|
--- |
|
license: mit |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: gpt2-sweep |
|
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-sweep |
|
|
|
This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.0808 |
|
- Accuracy: 0.8556 |
|
|
|
## 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: 2.294477077303931e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 1000 |
|
- num_epochs: 2.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 2.4827 | 0.19 | 1000 | 2.4565 | 0.8520 | |
|
| 2.6468 | 0.37 | 2000 | 2.3303 | 0.8530 | |
|
| 2.5106 | 0.56 | 3000 | 2.2487 | 0.8537 | |
|
| 2.0732 | 0.74 | 4000 | 2.2020 | 0.8541 | |
|
| 2.159 | 0.93 | 5000 | 2.1594 | 0.8545 | |
|
| 1.856 | 1.12 | 6000 | 2.1518 | 0.8548 | |
|
| 1.9138 | 1.3 | 7000 | 2.1261 | 0.8551 | |
|
| 1.8055 | 1.49 | 8000 | 2.1126 | 0.8552 | |
|
| 2.0385 | 1.67 | 9000 | 2.1008 | 0.8554 | |
|
| 1.9648 | 1.86 | 10000 | 2.0858 | 0.8555 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.26.0 |
|
- Pytorch 2.0.0+cu117 |
|
- Datasets 2.9.0 |
|
- Tokenizers 0.13.2 |
|
|