metadata
library_name: transformers
base_model: EleutherAI/pythia-14m
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mini-chennus
results: []
mini-chennus
This model is a fine-tuned version of EleutherAI/pythia-14m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.9861
- Accuracy: 0.0
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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.4394 | 0.1616 | 200 | 1.4008 | 0.0 |
| 1.2966 | 0.3231 | 400 | 1.2502 | 0.0 |
| 1.2088 | 0.4847 | 600 | 1.1922 | 0.0 |
| 1.1689 | 0.6462 | 800 | 1.1538 | 0.0001 |
| 1.1303 | 0.8078 | 1000 | 1.1333 | 0.0 |
| 1.1094 | 0.9693 | 1200 | 1.1012 | 0.0 |
| 1.0967 | 1.1309 | 1400 | 1.0750 | 0.0 |
| 1.0621 | 1.2924 | 1600 | 1.0659 | 0.0 |
| 1.0647 | 1.4540 | 1800 | 1.0566 | 0.0 |
| 1.0388 | 1.6155 | 2000 | 1.0452 | 0.0 |
| 1.0465 | 1.7771 | 2200 | 1.0266 | 0.0 |
| 1.0274 | 1.9386 | 2400 | 1.0119 | 0.0 |
| 1.0125 | 2.1002 | 2600 | 1.0084 | 0.0 |
| 1.0023 | 2.2617 | 2800 | 1.0002 | 0.0 |
| 1.0001 | 2.4233 | 3000 | 0.9968 | 0.0 |
| 0.9954 | 2.5848 | 3200 | 0.9912 | 0.0 |
| 0.9865 | 2.7464 | 3400 | 0.9853 | 0.0 |
| 0.9913 | 2.9079 | 3600 | 0.9861 | 0.0 |
Framework versions
- Transformers 4.57.2
- Pytorch 2.9.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1