---
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_e3_save5000_rp
  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_e3_save5000_rp

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: 2.2603

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 1.966         | 0.1908 | 1000  | 2.2603          |
| 1.3866        | 0.3815 | 2000  | 2.4390          |
| 0.8202        | 0.5723 | 3000  | 2.6035          |
| 0.497         | 0.7631 | 4000  | 2.8871          |
| 0.3141        | 0.9538 | 5000  | 3.1623          |
| 0.2115        | 1.1446 | 6000  | 3.3478          |
| 0.1859        | 1.3354 | 7000  | 3.4553          |
| 0.159         | 1.5261 | 8000  | 3.5514          |
| 0.1431        | 1.7169 | 9000  | 3.6509          |
| 0.127         | 1.9077 | 10000 | 3.7211          |
| 0.094         | 2.0984 | 11000 | 3.8280          |
| 0.0899        | 2.2892 | 12000 | 3.8603          |
| 0.0883        | 2.4800 | 13000 | 3.9257          |
| 0.0813        | 2.6707 | 14000 | 3.9864          |
| 0.0784        | 2.8615 | 15000 | 4.0649          |


### Framework versions

- Transformers 4.45.0
- Pytorch 2.3.0
- Datasets 2.14.4
- Tokenizers 0.20.3