---
license: apache-2.0
base_model: TinyLlama/TinyLlama_v1.1
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tinyllama_rm_sentiment_1b
  results: []
datasets:
- trl-internal-testing/sentiment-trl-style
---

<!-- 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. -->

# tinyllama_rm_sentiment_1b

This model is a fine-tuned version of [TinyLlama/TinyLlama_v1.1](https://huggingface.co./TinyLlama/TinyLlama_v1.1) on https://huggingface.co./datasets/trl-internal-testing/sentiment-trl-style.
It achieves the following results on the evaluation set:
- Loss: 0.6514
- Accuracy: 0.625

## Model description

Trained using:
```
python trl/examples/scripts/rm/rm.py \
--dataset_name trl-internal-testing/sentiment-trl-style \
--dataset_train_split train \
--dataset_eval_split test \
--model_name_or_path TinyLlama/TinyLlama_v1.1 \
--chat_template simple_concat \
--learning_rate 3e-6 \
--per_device_train_batch_size 32 \
--per_device_eval_batch_size 32 \
--gradient_accumulation_steps 1 \
--logging_steps 1 \
--eval_strategy steps \
--max_token_length 1024 \
--max_prompt_token_lenth 1024 \
--remove_unused_columns False \
--num_train_epochs 1 \
--eval_steps 100 \
 --output_dir models/ppo_torchtune/tinyllama/tinyllama_rm_sentiment_1b \
 --push_to_hub
```

on the "dataset-processor" branch of trl:

git clone -b "dataset-processor" https://github.com/huggingface/trl
## Intended uses & limitations

More information needed

## Training and evaluation data

https://huggingface.co./datasets/trl-internal-testing/sentiment-trl-style

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 3e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6033        | 0.6410 | 100  | 0.6514          | 0.625    |


### Framework versions

- Transformers 4.42.2
- Pytorch 2.2.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1