End of training

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+benchmarks.shelve.dat filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,181 @@
+---
+base_model: gpt2
+datasets:
+- wikimedia/wikipedia
+library_name: Distily
+license: mit
+tags:
+- bitnet
+- 1.58b
+- generated_from_trainer
+model-index:
+- name: verify_v0.3.0
+  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**: 124,439,808
+- **Data Type (dtype)**: torch.bfloat16
+- **Model Size**: 0.24 GB
+
+
+# Benchmark Metrics Comparison
+
+| Metric | dataset_sample_size=1000 | teacher |
+| :--- | :--- | :--- |
+| ai2_arc (acc) | 0.225 | 0.304 |
+| ai2_arc (acc_norm) | 0.251 | 0.309 |
+| ai2_arc (acc_norm_stderr) |  | 0.01 |
+| ai2_arc (acc_stderr) |  | 0.01 |
+| arc_challenge (acc) | 0.182 | 0.184 |
+| arc_challenge (acc_norm) | 0.223 | 0.214 |
+| arc_challenge (acc_norm_stderr) |  | 0.013 |
+| arc_challenge (acc_stderr) |  | 0.012 |
+| arc_easy (acc) | 0.268 | 0.424 |
+| arc_easy (acc_norm) | 0.278 | 0.405 |
+| arc_easy (acc_norm_stderr) |  | 0.016 |
+| arc_easy (acc_stderr) |  | 0.016 |
+| boolq (acc) | 0.375 | 0.541 |
+| boolq (acc_stderr) |  | 0.016 |
+| cola (mcc) | 0.0 | 0.009 |
+| cola (mcc_stderr) |  | 0.032 |
+| glue (acc) | 0.477 | 0.41 |
+| glue (acc_stderr) |  | 0.006 |
+| glue (f1) | 0.0 | 0.526 |
+| glue (f1_stderr) |  | 0.014 |
+| glue (mcc) | 0.0 | 0.009 |
+| glue (mcc_stderr) |  | 0.032 |
+| hellaswag (acc) | 0.287 | 0.337 |
+| hellaswag (acc_norm) | 0.269 | 0.384 |
+| hellaswag (acc_norm_stderr) |  | 0.015 |
+| hellaswag (acc_stderr) |  | 0.015 |
+| mnli (acc) | 0.335 | 0.323 |
+| mnli (acc_stderr) |  | 0.015 |
+| mnli_mismatch (acc) | 0.357 | 0.344 |
+| mnli_mismatch (acc_stderr) |  | 0.015 |
+| mrpc (acc) | 0.316 | 0.515 |
+| mrpc (acc_stderr) |  | 0.025 |
+| mrpc (f1) | 0.0 | 0.631 |
+| mrpc (f1_stderr) |  | 0.024 |
+| qnli (acc) | 0.527 | 0.472 |
+| qnli (acc_stderr) |  | 0.016 |
+| qqp (acc) | 0.673 | 0.34 |
+| qqp (acc_stderr) |  | 0.015 |
+| qqp (f1) | 0.0 | 0.483 |
+| qqp (f1_stderr) |  | 0.017 |
+| rte (acc) | 0.527 | 0.516 |
+| rte (acc_stderr) |  | 0.03 |
+| sst2 (acc) | 0.557 | 0.511 |
+| sst2 (acc_stderr) |  | 0.017 |
+| wikitext (bits_per_byte) | 1.979 |  |
+| wikitext (byte_perplexity) | 3.942 |  |
+| wikitext (word_perplexity) | 1533.0 |  |
+| wnli (acc) | 0.437 | 0.451 |
+| wnli (acc_stderr) |  | 0.059 |
+
+# Resource Usage Comparison
+
+- VRAM Use: 7.4923 GB
+
+# Distillation (Teacher -> Student) Architecture Difference:
+
+- **Architecture**: `GPT2LMHeadModel` -> `GPT2LMHeadModel`
+- **Total Parameters**: 124,439,808 -> 124,439,808
+- **Data Type (dtype)**: torch.bfloat16 -> torch.bfloat16
+- **Model Size**: 0.24 GB -> 0.24 GB
+
+<details>
+<summary>Module Diff Details</summary>
+
+```diff
+
+```
+
+</details>
+<br/>
+
+# Train Dataset
+Trained on 923,203 tokens from the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset.
+
+- Num Samples: `990`
+- Subset: `20231101.en`
+- Split: `train`
+
+
+# Training Objective
+
+```
+DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl))
+```
+
+# Hyperparameters
+The following hyperparameters were used during training:
+
+<details>
+<summary>Expand</summary>
+
+- learning_rate: `0.0001`
+- 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: `constant`
+- lr_scheduler_warmup_ratio: `0.2`
+- num_epochs: `1.0`
+- distillation_objective: `DistillationObjective(logits_loss_component=LossComponent(label=logits, weight=1, loss_fn=kl))`
+- train_embeddings: `True`
+- lr_scheduler: `<torch.optim.lr_scheduler.LambdaLR object at 0x7ff7e81bb7c0>`
+- student_model_name_or_path: `None`
+- student_config_name_or_path: `None`
+- student_model_config: `None`
+- reinitialize_weights: `None`
+- copy_teacher_modules: `[('lm_head', False)]`
+- student_model_as_bitnet: `True`
+- student_model_compile: `False`
+- dropout: `None`
+- teacher_model_name_or_path: `gpt2`
+- teacher_load_in_8bit: `False`
+- teacher_load_in_4bit: `False`
+- teacher_model_compile: `False`
+- dataset_uri: `wikimedia/wikipedia`
+- dataset_subset: `20231101.en`
+- dataset_split: `train`
+- dataset_column_name: `text`
+- dataset_sample_size: `1000`
+- dataset_test_size: `0.01`
+- gradient_accumulation_steps: `1`
+- weight_decay: `0.0`
+- max_grad_norm: `1.0`
+- warmup_ratio: `0.2`
+- warmup_steps: `0`
+- gradient_checkpointing: `True`
+
+</details>
+<br/>
+
+
+# Framework Versions
+- Distily 0.3.0
+- Transformers 4.44.2
+- Pytorch 2.3.0
+- Datasets 2.21.0

benchmarks.shelve.bak

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generation_config.json

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+  "transformers_version": "4.44.2"
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