---
library_name: transformers
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- generator
model-index:
- name: IRL_iter0_best_of_16_spin_iter0_epoch_5_saving
  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. -->

# IRL_iter0_best_of_16_spin_iter0_epoch_5_saving

This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the d, the a, the t, the a, the _, the g, the e, the n, the e, the r, the a, the t, the e, the d, the /, the s, the p, the i, the n, the _, the i, the t, the e, the r, the 0, the _, the b, the e, the s, the t, the _, the o, the f, the _, the 1, the 6, the /, the t, the o, the p, the 1, the _, the s, the e, the l, the e, the c, the t, the e, the d, the _, the I, the R, the L, the _, the r, the e, the w, the a, the r, the d, the _, the s, the e, the l, the e, the c, the t, the e and the d datasets.
It achieves the following results on the evaluation set:
- Loss: 0.0396

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.0895        | 1.0   | 79   | 0.7223          |
| 0.6454        | 2.0   | 158  | 0.3317          |
| 0.2926        | 3.0   | 237  | 0.1293          |
| 0.1048        | 4.0   | 316  | 0.0542          |
| 0.0465        | 5.0   | 395  | 0.0396          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1