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README.md

@@ -0,0 +1,61 @@
+---
+base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T
+tags:
+- generated_from_trainer
+model-index:
+- name: out_fft
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+# out_fft
+
+This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8797
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 2.0547        | 0.0   | 1    | 2.0329          |
+| 1.9388        | 0.25  | 3087 | 1.0713          |
+| 1.4746        | 0.5   | 6174 | 0.9426          |
+| 1.1822        | 0.75  | 9261 | 0.8797          |
+
+
+### Framework versions
+
+- Transformers 4.37.0.dev0
+- Pytorch 2.0.1
+- Datasets 2.15.0
+- Tokenizers 0.15.0

checkpoint-12345/config.json

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+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
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+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 22,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

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config.json

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+{
+  "_name_or_path": "TinyLlama/TinyLlama-1.1B-intermediate-step-955k-token-2T",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
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+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 22,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
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+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

generation_config.json

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+  "eos_token_id": 2,
+  "max_length": 2048,
+  "pad_token_id": 0,
+  "transformers_version": "4.37.0.dev0"
+}

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+    "rstrip": false,
+    "single_word": false
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+    "single_word": false
+  }
+}

tinyllama-slider-empathy/.gitattributes

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tinyllama-slider-empathy/README.md

@@ -0,0 +1,98 @@
+---
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: awilliamson/tinyllama-slider
+model-index:
+- name: empathy-lora-out
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+# empathy-lora-out
+
+This model is a fine-tuned version of [awilliamson/tinyllama-slider](https://huggingface.co/awilliamson/tinyllama-slider) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.2988
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 25
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.5961        | 0.03  | 1    | 1.5286          |
+| 1.6946        | 0.27  | 8    | 1.5283          |
+| 1.5327        | 0.54  | 16   | 1.5186          |
+| 1.4197        | 0.81  | 24   | 1.4726          |
+| 1.4979        | 1.03  | 32   | 1.4323          |
+| 1.3198        | 1.3   | 40   | 1.3997          |
+| 1.4632        | 1.57  | 48   | 1.3762          |
+| 1.3486        | 1.84  | 56   | 1.3547          |
+| 1.3901        | 2.08  | 64   | 1.3386          |
+| 1.3964        | 2.35  | 72   | 1.3291          |
+| 1.3844        | 2.62  | 80   | 1.3184          |
+| 1.2799        | 2.89  | 88   | 1.3108          |
+| 1.3213        | 3.13  | 96   | 1.3061          |
+| 1.0652        | 3.39  | 104  | 1.3050          |
+| 1.1837        | 3.66  | 112  | 1.3024          |
+| 1.4713        | 3.93  | 120  | 1.2992          |
+| 1.3074        | 4.17  | 128  | 1.2979          |
+| 1.2039        | 4.44  | 136  | 1.2993          |
+| 1.1574        | 4.71  | 144  | 1.2988          |
+
+
+### Framework versions
+
+- Transformers 4.37.0.dev0
+- Pytorch 2.0.1
+- Datasets 2.15.0
+- Tokenizers 0.15.0
+## Training procedure
+
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- load_in_8bit: True
+- load_in_4bit: False
+- llm_int8_threshold: 6.0
+- llm_int8_skip_modules: None
+- llm_int8_enable_fp32_cpu_offload: False
+- llm_int8_has_fp16_weight: False
+- bnb_4bit_quant_type: fp4
+- bnb_4bit_use_double_quant: False
+- bnb_4bit_compute_dtype: float32
+
+### Framework versions
+
+
+- PEFT 0.6.0

tinyllama-slider-empathy/adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "awilliamson/tinyllama-slider",
+  "bias": "none",
+  "fan_in_fan_out": null,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "q_proj",
+    "gate_proj",
+    "o_proj",
+    "down_proj",
+    "v_proj",
+    "up_proj",
+    "k_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

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tinyllama-slider-empathy/config.json

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+{
+  "_name_or_path": "awilliamson/tinyllama-slider",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
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+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 22,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
+  "quantization_config": {
+    "bnb_4bit_compute_dtype": "float32",
+    "bnb_4bit_quant_type": "fp4",
+    "bnb_4bit_use_double_quant": false,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
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+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": false,
+    "load_in_8bit": true,
+    "quant_method": "bitsandbytes"
+  },
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

tinyllama-slider-empathy/special_tokens_map.json

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+}

tinyllama-slider-empathy/tokenizer.model

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tinyllama-slider-empathy/tokenizer_config.json

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+{
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+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
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+}

tinyllama-slider-humor/.gitattributes

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tinyllama-slider-humor/README.md

@@ -0,0 +1,99 @@
+---
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: awilliamson/tinyllama-slider
+model-index:
+- name: humor-lora-out
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
+# humor-lora-out
+
+This model is a fine-tuned version of [awilliamson/tinyllama-slider](https://huggingface.co/awilliamson/tinyllama-slider) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.3681
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 2
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 25
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.694         | 0.03  | 1    | 1.5624          |
+| 1.8318        | 0.25  | 8    | 1.5622          |
+| 1.601         | 0.51  | 16   | 1.5545          |
+| 1.5841        | 0.76  | 24   | 1.5179          |
+| 1.4322        | 1.02  | 32   | 1.4899          |
+| 1.6246        | 1.24  | 40   | 1.4707          |
+| 1.5611        | 1.49  | 48   | 1.4479          |
+| 1.6092        | 1.75  | 56   | 1.4295          |
+| 1.4446        | 2.0   | 64   | 1.4150          |
+| 1.5642        | 2.24  | 72   | 1.4007          |
+| 1.4571        | 2.49  | 80   | 1.3897          |
+| 1.5188        | 2.75  | 88   | 1.3823          |
+| 1.2361        | 3.0   | 96   | 1.3776          |
+| 1.5355        | 3.21  | 104  | 1.3747          |
+| 1.0987        | 3.47  | 112  | 1.3735          |
+| 1.3499        | 3.72  | 120  | 1.3703          |
+| 1.2923        | 3.98  | 128  | 1.3688          |
+| 1.2019        | 4.2   | 136  | 1.3684          |
+| 1.5106        | 4.45  | 144  | 1.3689          |
+| 1.3429        | 4.71  | 152  | 1.3681          |
+
+
+### Framework versions
+
+- Transformers 4.37.0.dev0
+- Pytorch 2.0.1
+- Datasets 2.15.0
+- Tokenizers 0.15.0
+## Training procedure
+
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- load_in_8bit: True
+- load_in_4bit: False
+- llm_int8_threshold: 6.0
+- llm_int8_skip_modules: None
+- llm_int8_enable_fp32_cpu_offload: False
+- llm_int8_has_fp16_weight: False
+- bnb_4bit_quant_type: fp4
+- bnb_4bit_use_double_quant: False
+- bnb_4bit_compute_dtype: float32
+
+### Framework versions
+
+
+- PEFT 0.6.0

tinyllama-slider-humor/adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "awilliamson/tinyllama-slider",
+  "bias": "none",
+  "fan_in_fan_out": null,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "o_proj",
+    "gate_proj",
+    "up_proj",
+    "down_proj",
+    "k_proj",
+    "q_proj"
+  ],
+  "task_type": "CAUSAL_LM"
+}

tinyllama-slider-humor/adapter_model.bin

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+size 101036253

tinyllama-slider-humor/config.json

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+{
+  "_name_or_path": "awilliamson/tinyllama-slider",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 5632,
+  "max_position_embeddings": 2048,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 22,
+  "num_key_value_heads": 4,
+  "pretraining_tp": 1,
+  "quantization_config": {
+    "bnb_4bit_compute_dtype": "float32",
+    "bnb_4bit_quant_type": "fp4",
+    "bnb_4bit_use_double_quant": false,
+    "llm_int8_enable_fp32_cpu_offload": false,
+    "llm_int8_has_fp16_weight": false,
+    "llm_int8_skip_modules": null,
+    "llm_int8_threshold": 6.0,
+    "load_in_4bit": false,
+    "load_in_8bit": true,
+    "quant_method": "bitsandbytes"
+  },
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.37.0.dev0",
+  "use_cache": false,
+  "vocab_size": 32000
+}

tinyllama-slider-humor/special_tokens_map.json

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+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tinyllama-slider-humor/tokenizer.model

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+size 499723

tinyllama-slider-humor/tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": false,
+  "model_max_length": 1000000000000000019884624838656,
+  "pad_token": "</s>",
+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "trust_remote_code": false,
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false,
+  "use_fast": true
+}

tokenizer.model

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+oid sha256:9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
+size 499723

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+  "bos_token": "<s>",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
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+  "padding_side": "right",
+  "sp_model_kwargs": {},
+  "spaces_between_special_tokens": false,
+  "tokenizer_class": "LlamaTokenizer",
+  "trust_remote_code": false,
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false,
+  "use_fast": true
+}