---
library_name: transformers
base_model: /fs-computility/plm/linzhouhan/daibeiya/models/gpt2
tags:
- generated_from_trainer
datasets:
- openwebtext
model-index:
- name: gpt2_base_contextlm_l0212_add_lnnorm_wodetach_v2_lr_bf16_lr1e-3
  results: []
---

<!-- 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. -->

# gpt2_base_contextlm_l0212_add_lnnorm_wodetach_v2_lr_bf16_lr1e-3

This model is a fine-tuned version of [/fs-computility/plm/linzhouhan/daibeiya/models/gpt2](https://huggingface.co//fs-computility/plm/linzhouhan/daibeiya/models/gpt2) on the openwebtext dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0300

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- total_eval_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.95) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 3.9616        | 0.0580 | 1000  | 3.8911          |
| 3.5512        | 0.1160 | 2000  | 3.4861          |
| 3.4279        | 0.1741 | 3000  | 3.3560          |
| 3.3471        | 0.2321 | 4000  | 3.2811          |
| 3.2957        | 0.2901 | 5000  | 3.2321          |
| 3.2677        | 0.3481 | 6000  | 3.1945          |
| 3.225         | 0.4062 | 7000  | 3.1653          |
| 3.2051        | 0.4642 | 8000  | 3.1390          |
| 3.1816        | 0.5222 | 9000  | 3.1161          |
| 3.1583        | 0.5802 | 10000 | 3.0971          |
| 3.1464        | 0.6383 | 11000 | 3.0794          |
| 3.1365        | 0.6963 | 12000 | 3.0645          |
| 3.1256        | 0.7543 | 13000 | 3.0509          |
| 3.1073        | 0.8123 | 14000 | 3.0417          |
| 3.108         | 0.8703 | 15000 | 3.0349          |
| 3.098         | 0.9284 | 16000 | 3.0312          |
| 3.092         | 0.9864 | 17000 | 3.0301          |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.3.0+cu121
- Datasets 4.0.0
- Tokenizers 0.21.4