---
license: apache-2.0
base_model: mnoukhov/pythia2.8b-sft-tldr
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: pythia2.8b-rm-tldr6.9b
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# pythia2.8b-rm-tldr6.9b

This model is a fine-tuned version of [mnoukhov/pythia2.8b-sft-tldr](https://huggingface.co/mnoukhov/pythia2.8b-sft-tldr) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3979
- Accuracy: 0.8129

## 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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5048        | 0.2006 | 291  | 0.4736          | 0.7684   |
| 0.4188        | 0.4011 | 582  | 0.4287          | 0.7951   |
| 0.3628        | 0.6017 | 873  | 0.4141          | 0.8028   |
| 0.3203        | 0.8022 | 1164 | 0.3979          | 0.8129   |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1