End of training

README.md

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+---
+base_model: distilbert/distilgpt2
+datasets:
+- wikimedia/wikipedia
+library_name: Distily
+license: apache-2.0
+tags:
+- generated_from_trainer
+model-index:
+- name: distily_validate_extra_grad_stats3
+  results: []
+---
+
+
+# Summary
+
+Distilled with [Distily](https://github.com/lapp0/distily) library
+using teacher model [gpt2](https://huggingface.co/gpt2)
+on dataset [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia).
+
+<!-- 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.
+
+# Model description
+
+More information needed
+
+# Intended uses & limitations
+
+More information needed
+-->
+
+# Model Architecture:
+- **Architecture**: `GPT2LMHeadModel`
+- **Total Parameters**: 81,912,576
+- **Data Type (dtype)**: torch.bfloat16
+- **Model Size**: 0.16 GB
+
+
+# Benchmark Metrics Comparison
+
+| Metric |  |
+| :--- |
+
+# Resource Usage Comparison
+
+- VRAM Use: 7.4255 GB
+
+# Distillation (Teacher -> Student) Architecture Difference:
+
+- **Architecture**: `GPT2LMHeadModel` -> `GPT2LMHeadModel`
+- **Total Parameters**: 124,439,808 -> 81,912,576
+- **Data Type (dtype)**: torch.bfloat16 -> torch.bfloat16
+- **Model Size**: 0.24 GB -> 0.16 GB
+
+<details>
+<summary>Module Diff Details</summary>
+
+```diff
+--- teacher model modules
++++ student model modules
+@@ -4,7 +4,7 @@
+     (wpe): Embedding(1024, 768)
+     (drop): Dropout(p=0.1, inplace=False)
+     (h): ModuleList(
+-      (0-11): 12 x GPT2Block(
++      (0-5): 6 x GPT2Block(
+         (ln_1): LayerNorm((768,), eps=1e-05, elementwise_affine=True)
+         (attn): GPT2FlashAttention2(
+           (c_attn): Conv1D()
+
+```
+
+</details>
+<br/>
+
+# Train Dataset
+Trained on 6,816,188 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
+
+- Num Samples: `9,900`
+- Subset: `20231101.en`
+- Split: `train`
+
+
+# Training Objective
+
+```
+DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5, loss_fn=raw_mse, layer_mapper=layer-2, projector=orthogonal))
+```
+
+# Hyperparameters
+The following hyperparameters were used during training:
+
+<details>
+<summary>Expand</summary>
+
+- learning_rate: `0.0002`
+- train_batch_size: `4`
+- eval_batch_size: `8`
+- seed: `42`
+- optimizer: `Adam with betas=(0.9,0.999) and epsilon=1e-08`
+- lr_scheduler_type: `polynomial`
+- num_epochs: `1.0`
+- distillation_objective: `DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl), attn_loss_component=LossComponent(label=attn, weight=5, loss_fn=raw_mse, layer_mapper=layer-2, projector=orthogonal))`
+- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7f53f2d5d870>`
+- student_model_name_or_path: `None`
+- student_config_name_or_path: `distilbert/distilgpt2`
+- student_model_config: `None`
+- reinitialize_weights: `None`
+- copy_teacher_modules: `[('lm_head', False)]`
+- student_model_as_bitnet: `False`
+- teacher_model_name_or_path: `gpt2`
+- teacher_load_in_8bit: `False`
+- teacher_load_in_4bit: `False`
+- dataset_uri: `wikimedia/wikipedia`
+- dataset_subset: `20231101.en`
+- dataset_split: `train`
+- dataset_column_name: `text`
+- dataset_sample_size: `10000`
+- dataset_test_size: `0.01`
+- gradient_accumulation_steps: `1`
+- weight_decay: `0.0`
+- max_grad_norm: `1.0`
+- warmup_ratio: `0`
+- warmup_steps: `0`
+- gradient_checkpointing: `True`
+
+</details>
+<br/>
+
+
+# Framework Versions
+- Distily 0.4.1
+- Transformers 4.44.2
+- Pytorch 2.3.0
+- Datasets 2.21.0

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 50256,
+  "eos_token_id": 50256,
+  "transformers_version": "4.44.2"
+}

logs/attn_projector=orthogonal, attn_weight=5, extra_grad_stats=True, learning_rate=0.0002, per_device_train_batch_size=4, warmup_ratio=0/events.out.tfevents.1725311283.261a4d6fb516

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