---
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