Downloads · 30 days
9
36% of all-time downloads
gpt2_for_whole_train_result_1_2bce
CatBarks/gpt2_for_whole_train_result_1_2bce
gpt2_for_whole_train_result_1_2bce is a machine learning model from CatBarks. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
All-time downloads
25
Public
Parameters
124M
498 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors498 MB · 100%
At a glance
- License
- mit
- Model type
- gpt2
- Access
- Public
- Created
- Jan 28, 2025
- Updated
- Jan 28, 2025
- SHA
- ce7e4242
Base models
Model card
From the Hugging Face model README
<!-- 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_for_whole_train_result_1_2bce
This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0290
- Accuracy: 0.995
- F1: 0.9953
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 4096
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 1.7296 | 6.8817 | 50 | 0.7674 | 0.6645 | 0.7317 |
| 0.2968 | 13.7634 | 100 | 0.1240 | 0.9565 | 0.9605 |
| 0.0564 | 20.6452 | 150 | 0.0491 | 0.986 | 0.9869 |
| 0.0206 | 27.5269 | 200 | 0.0351 | 0.993 | 0.9934 |
| 0.0081 | 34.4086 | 250 | 0.0321 | 0.994 | 0.9944 |
| 0.0041 | 41.2903 | 300 | 0.0370 | 0.993 | 0.9935 |
| 0.002 | 48.1720 | 350 | 0.0334 | 0.995 | 0.9953 |
| 0.0017 | 55.0538 | 400 | 0.0339 | 0.9955 | 0.9958 |
| 0.001 | 61.9355 | 450 | 0.0326 | 0.995 | 0.9953 |
| 0.0005 | 68.8172 | 500 | 0.0371 | 0.996 | 0.9963 |
| 0.0005 | 75.6989 | 550 | 0.0333 | 0.996 | 0.9962 |
| 0.0007 | 82.5806 | 600 | 0.0344 | 0.9945 | 0.9948 |
| 0.0004 | 89.4624 | 650 | 0.0512 | 0.9925 | 0.9930 |
| 0.0024 | 96.3441 | 700 | 0.0290 | 0.995 | 0.9953 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
- Type
- gpt2
- License
- mit
- Created
- Jan 28, 2025
- Updated
- Jan 28, 2025