---
library_name: transformers
license: llama3.2
base_model: meta-llama/Llama-3.2-1B
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: rationale_model_e15
  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. -->

# rationale_model_e15

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B](https://huggingface.co/meta-llama/Llama-3.2-1B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1070

## 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 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: 3.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 2.1363        | 0.0954 | 500   | 2.1185          |
| 1.7868        | 0.1908 | 1000  | 2.1070          |
| 1.5132        | 0.2862 | 1500  | 2.1743          |
| 1.238         | 0.3815 | 2000  | 2.2694          |
| 0.9723        | 0.4769 | 2500  | 2.3214          |
| 0.7249        | 0.5723 | 3000  | 2.4423          |
| 0.5657        | 0.6677 | 3500  | 2.5636          |
| 0.4404        | 0.7631 | 4000  | 2.6851          |
| 0.3192        | 0.8585 | 4500  | 2.8630          |
| 0.2676        | 0.9538 | 5000  | 2.9741          |
| 0.2057        | 1.0492 | 5500  | 3.0958          |
| 0.1792        | 1.1446 | 6000  | 3.1219          |
| 0.1691        | 1.2400 | 6500  | 3.1735          |
| 0.1597        | 1.3354 | 7000  | 3.2299          |
| 0.1516        | 1.4308 | 7500  | 3.2997          |
| 0.1422        | 1.5261 | 8000  | 3.2759          |
| 0.1372        | 1.6215 | 8500  | 3.3557          |
| 0.1301        | 1.7169 | 9000  | 3.4023          |
| 0.1229        | 1.8123 | 9500  | 3.4617          |
| 0.1183        | 1.9077 | 10000 | 3.4668          |
| 0.1119        | 2.0031 | 10500 | 3.5609          |
| 0.0924        | 2.0984 | 11000 | 3.5975          |
| 0.0926        | 2.1938 | 11500 | 3.6429          |
| 0.089         | 2.2892 | 12000 | 3.6586          |
| 0.0881        | 2.3846 | 12500 | 3.6920          |
| 0.0861        | 2.4800 | 13000 | 3.7656          |
| 0.0835        | 2.5754 | 13500 | 3.7939          |
| 0.0803        | 2.6707 | 14000 | 3.8398          |
| 0.0797        | 2.7661 | 14500 | 3.8909          |
| 0.0774        | 2.8615 | 15000 | 3.9238          |
| 0.0759        | 2.9569 | 15500 | 3.9394          |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.3.0
- Datasets 2.14.4
- Tokenizers 0.20.3