---
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: tinyllama-chat-mine-dpo
  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. -->

# tinyllama-chat-mine-dpo

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6240
- Rewards/chosen: -0.7007
- Rewards/rejected: -0.9684
- Rewards/accuracies: 0.6825
- Rewards/margins: 0.2677
- Logps/rejected: -395.3808
- Logps/chosen: -412.6868
- Logits/rejected: -2.7107
- Logits/chosen: -2.7399

## 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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6685        | 0.2093 | 100  | 0.6694          | -0.1299        | -0.1943          | 0.6528             | 0.0644          | -317.9682      | -355.6027    | -2.9255         | -2.9507       |
| 0.642         | 0.4186 | 200  | 0.6407          | -0.4273        | -0.6175          | 0.6726             | 0.1902          | -360.2873      | -385.3470    | -2.7926         | -2.8208       |
| 0.6285        | 0.6279 | 300  | 0.6331          | -0.4723        | -0.6951          | 0.6647             | 0.2228          | -368.0482      | -389.8438    | -2.7731         | -2.8012       |
| 0.6222        | 0.8373 | 400  | 0.6240          | -0.7007        | -0.9684          | 0.6825             | 0.2677          | -395.3808      | -412.6868    | -2.7107         | -2.7399       |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1