peft safetensors generated_from_trainer base_model:microsoft/phi-2 license:mit region:us
---
license: mit 
library_name: peft
tags:
- generated_from_trainer
base_model: microsoft/phi-2
model-index:
- name: phi2-english-to-hinglish-translation
  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. -->

# phi2-english-to-hinglish-translation

This model is a fine-tuned version of [microsoft/phi-2](https://huggingface.co/microsoft/phi-2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3394
- Rouge Scores: {'rouge1': 0.02194963696306387, 'rouge2': 0.017844397420545253, 'rougeL': 0.017985463648805815, 'rougeLsum': 0.02198801722885821}
- Bleu Scores: [0.0141983812922229, 0.013783602019353523, 0.013237039007079092, 0.012647324457245113]
- Gen Len: 2048.0

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge Scores                                                                                                               | Bleu Scores                                                                              | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:--------------------------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------------------------------:|:-------:|
| 1.6688        | 1.0   | 500  | 1.4150          | {'rouge1': 0.021944939879946292, 'rouge2': 0.017781155558600512, 'rougeL': 0.017866554441667286, 'rougeLsum': 0.02197862373873669} | [0.014214089766333284, 0.013807603949625002, 0.013250971870467268, 0.012646602626664907] | 2048.0  |
| 1.2148        | 2.0   | 1000 | 1.3394          | {'rouge1': 0.02194963696306387, 'rouge2': 0.017844397420545253, 'rougeL': 0.017985463648805815, 'rougeLsum': 0.02198801722885821}  | [0.0141983812922229, 0.013783602019353523, 0.013237039007079092, 0.012647324457245113]   | 2048.0  |


### Framework versions

- PEFT 0.8.2
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.16.2.dev0
- Tokenizers 0.15.1