llama3-2k-spa_2 / README.md
Seohyeong Lee
add dataset
53e8f58
---
base_model: save_model/llama3-2k-spa_1
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- datasets/training-llama3-2k-spa_2
model-index:
- name: llama3-2k-spa_2
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. -->
# llama3-2k-spa_2
This model is a fine-tuned version of [save_model/llama3-2k-spa_1](https://huggingface.co/save_model/llama3-2k-spa_1) on the datasets/training-llama3-2k-spa_2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9255
- Rewards/chosen: -7.0304
- Rewards/rejected: -7.9655
- Rewards/accuracies: 0.6667
- Rewards/margins: 0.9351
- Rewards/mix Margin: 0.9351
- Logps/rejected: -380.0901
- Logps/chosen: -401.9111
- Logits/rejected: -0.3285
- Logits/chosen: -0.3819
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- total_eval_batch_size: 2
- 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 | Rewards/mix Margin | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.3277 | 0.8 | 1000 | 0.9255 | -7.0304 | -7.9655 | 0.6667 | 0.9351 | 0.9351 | -380.0901 | -401.9111 | -0.3285 | -0.3819 |
### Framework versions
- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2