|
--- |
|
license: apache-2.0 |
|
base_model: EleutherAI/pythia-160m |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: python_and_text_pythia_160m |
|
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. --> |
|
|
|
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhenwu/code-text-pretraining/runs/oz6oj1oi) |
|
# python_and_text_pythia_160m |
|
|
|
This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.6491 |
|
- Accuracy: 0.1972 |
|
- Num Input Tokens Seen: 1941504 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 4 |
|
- eval_batch_size: 4 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- num_devices: 2 |
|
- total_train_batch_size: 8 |
|
- total_eval_batch_size: 8 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_ratio: 0.03 |
|
- num_epochs: 3.0 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Input Tokens Seen | |
|
|:-------------:|:------:|:----:|:---------------:|:--------:|:-----------------:| |
|
| No log | 0 | 0 | 9.8144 | 0.1972 | 0 | |
|
| 2.0211 | 0.6329 | 50 | 1.9535 | 0.1268 | 409600 | |
|
| 1.916 | 1.2658 | 100 | 1.6972 | 0.1972 | 819200 | |
|
| 1.6616 | 1.8987 | 150 | 1.6491 | 0.1972 | 1228800 | |
|
| 1.565 | 2.5316 | 200 | 1.6664 | 0.1408 | 1638400 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.43.2 |
|
- Pytorch 2.4.0 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
