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End of training

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  1. README.md +18 -18
README.md CHANGED
@@ -1,13 +1,13 @@
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  ---
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  library_name: peft
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- base_model: samoline/tensoralchemistdev01__sv9-with-tokenizer
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  tags:
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  - axolotl
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  - generated_from_trainer
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  datasets:
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- - Aivesa/dataset_12076561-6ae2-493b-9bce-28ba02fe74db
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  model-index:
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- - name: bc9b7646-068e-4da9-8c0f-158538d35d1c
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  results: []
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  ---
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@@ -20,18 +20,18 @@ should probably proofread and complete it, then remove this comment. -->
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  axolotl version: `0.6.0`
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  ```yaml
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  adapter: lora
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- base_model: samoline/tensoralchemistdev01__sv9-with-tokenizer
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  bf16: auto
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  chat_template: llama3
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  dataset_prepared_path: /workspace/axolotl/data/prepared
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  datasets:
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  - ds_type: json
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  format: custom
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- path: Aivesa/dataset_12076561-6ae2-493b-9bce-28ba02fe74db
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  type:
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- field_input: input
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- field_instruction: instruction
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- field_output: output
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  system_format: '{system}'
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  system_prompt: ''
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  debug: null
@@ -47,7 +47,7 @@ fsdp_config: null
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  gradient_accumulation_steps: 4
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  gradient_checkpointing: false
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  group_by_length: false
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- hub_model_id: Aivesa/bc9b7646-068e-4da9-8c0f-158538d35d1c
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  hub_private_repo: true
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  hub_repo: null
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  hub_strategy: checkpoint
@@ -79,7 +79,7 @@ save_safetensors: true
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  saves_per_epoch: 4
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  sequence_len: 512
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  special_tokens:
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- pad_token: <|endoftext|>
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  strict: false
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  tf32: false
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  tokenizer_type: AutoTokenizer
@@ -89,10 +89,10 @@ use_accelerate: true
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  val_set_size: 0.05
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  wandb_entity: null
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  wandb_mode: online
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- wandb_name: 12076561-6ae2-493b-9bce-28ba02fe74db
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  wandb_project: Gradients-On-Demand
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  wandb_run: your_name
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- wandb_runid: 12076561-6ae2-493b-9bce-28ba02fe74db
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  warmup_steps: 10
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  weight_decay: 0.0
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  xformers_attention: null
@@ -101,11 +101,11 @@ xformers_attention: null
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  </details><br>
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- # bc9b7646-068e-4da9-8c0f-158538d35d1c
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- This model is a fine-tuned version of [samoline/tensoralchemistdev01__sv9-with-tokenizer](https://huggingface.co/samoline/tensoralchemistdev01__sv9-with-tokenizer) on the Aivesa/dataset_12076561-6ae2-493b-9bce-28ba02fe74db dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.4667
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  ## Model description
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@@ -139,9 +139,9 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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- | 1.4983 | 0.0006 | 3 | 1.6784 |
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- | 1.3833 | 0.0012 | 6 | 1.6113 |
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- | 1.1765 | 0.0018 | 9 | 1.4667 |
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  ### Framework versions
 
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  ---
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  library_name: peft
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+ base_model: NousResearch/CodeLlama-13b-hf
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  tags:
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  - axolotl
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  - generated_from_trainer
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  datasets:
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+ - Aivesa/dataset_4bea4578-524c-4430-8071-bbcf24df00eb
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  model-index:
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+ - name: e2777369-66dd-42d7-90e2-868e01499551
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  results: []
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  ---
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  axolotl version: `0.6.0`
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  ```yaml
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  adapter: lora
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+ base_model: NousResearch/CodeLlama-13b-hf
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  bf16: auto
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  chat_template: llama3
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  dataset_prepared_path: /workspace/axolotl/data/prepared
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  datasets:
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  - ds_type: json
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  format: custom
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+ path: Aivesa/dataset_4bea4578-524c-4430-8071-bbcf24df00eb
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  type:
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+ field_input: text
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+ field_instruction: intent
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+ field_output: slots
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  system_format: '{system}'
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  system_prompt: ''
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  debug: null
 
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  gradient_accumulation_steps: 4
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  gradient_checkpointing: false
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  group_by_length: false
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+ hub_model_id: Aivesa/e2777369-66dd-42d7-90e2-868e01499551
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  hub_private_repo: true
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  hub_repo: null
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  hub_strategy: checkpoint
 
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  saves_per_epoch: 4
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  sequence_len: 512
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  special_tokens:
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+ pad_token: </s>
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  strict: false
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  tf32: false
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  tokenizer_type: AutoTokenizer
 
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  val_set_size: 0.05
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  wandb_entity: null
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  wandb_mode: online
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+ wandb_name: 4bea4578-524c-4430-8071-bbcf24df00eb
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  wandb_project: Gradients-On-Demand
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  wandb_run: your_name
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+ wandb_runid: 4bea4578-524c-4430-8071-bbcf24df00eb
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  warmup_steps: 10
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  weight_decay: 0.0
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  xformers_attention: null
 
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  </details><br>
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+ # e2777369-66dd-42d7-90e2-868e01499551
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+ This model is a fine-tuned version of [NousResearch/CodeLlama-13b-hf](https://huggingface.co/NousResearch/CodeLlama-13b-hf) on the Aivesa/dataset_4bea4578-524c-4430-8071-bbcf24df00eb dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.2549
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:------:|:----:|:---------------:|
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+ | 13.5248 | 0.0045 | 3 | 2.8330 |
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+ | 12.1843 | 0.0089 | 6 | 2.5730 |
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+ | 6.9279 | 0.0134 | 9 | 1.2549 |
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  ### Framework versions