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---
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
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