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---
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
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