File size: 3,584 Bytes
81121bf 84c353c 81121bf 84c353c 81121bf |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 |
---
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_stats2
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: 7.4250 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 6,814,337 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 0x7f9748205ed0>`
- 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
|