metadata
library_name: transformers
license: apache-2.0
base_model: EleutherAI/pythia-160m
tags:
- generated_from_trainer
model-index:
- name: pythia_160m_sft
results: []
datasets:
- tatsu-lab/alpaca_farm
pythia_160m_sft
This model is a fine-tuned version of EleutherAI/pythia-160m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.9831
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.2935 | 0.0889 | 100 | 2.1426 |
| 2.153 | 0.1778 | 200 | 2.0977 |
| 2.1432 | 0.2667 | 300 | 2.0771 |
| 2.1131 | 0.3556 | 400 | 2.0633 |
| 2.0885 | 0.4444 | 500 | 2.0510 |
| 2.0956 | 0.5333 | 600 | 2.0403 |
| 2.0647 | 0.6222 | 700 | 2.0354 |
| 2.0498 | 0.7111 | 800 | 2.0273 |
| 2.0317 | 0.8 | 900 | 2.0202 |
| 2.0226 | 0.8889 | 1000 | 2.0150 |
| 1.992 | 0.9778 | 1100 | 2.0114 |
| 1.9639 | 1.0667 | 1200 | 2.0088 |
| 1.9302 | 1.1556 | 1300 | 2.0051 |
| 1.9381 | 1.2444 | 1400 | 2.0028 |
| 1.9595 | 1.3333 | 1500 | 2.0009 |
| 1.9325 | 1.4222 | 1600 | 1.9998 |
| 1.9481 | 1.5111 | 1700 | 1.9981 |
| 1.9572 | 1.6 | 1800 | 1.9956 |
| 1.9456 | 1.6889 | 1900 | 1.9944 |
| 1.9565 | 1.7778 | 2000 | 1.9922 |
| 1.9507 | 1.8667 | 2100 | 1.9905 |
| 1.9247 | 1.9556 | 2200 | 1.9881 |
| 1.8998 | 2.0444 | 2300 | 1.9874 |
| 1.9102 | 2.1333 | 2400 | 1.9873 |
| 1.8842 | 2.2222 | 2500 | 1.9876 |
| 1.876 | 2.3111 | 2600 | 1.9863 |
| 1.9001 | 2.4 | 2700 | 1.9856 |
| 1.8725 | 2.4889 | 2800 | 1.9859 |
| 1.868 | 2.5778 | 2900 | 1.9845 |
| 1.8803 | 2.6667 | 3000 | 1.9844 |
| 1.9002 | 2.7556 | 3100 | 1.9838 |
| 1.8941 | 2.8444 | 3200 | 1.9839 |
| 1.8548 | 2.9333 | 3300 | 1.9831 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3