---
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).
# 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
Module Diff Details
```diff
```
# 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:
Expand
- 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: ``
- 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`
# Framework Versions
- Distily 0.3.0
- Transformers 4.44.2
- Pytorch 2.3.0
- Datasets 2.21.0