---
library_name: transformers
license: apache-2.0
base_model: LingoIITGN/ganga-1b
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: ganga-idiom-finetune
  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. -->

# ganga-idiom-finetune

This model is a fine-tuned version of [LingoIITGN/ganga-1b](https://huggingface.co/LingoIITGN/ganga-1b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6450
- Rouge1: 0.4650
- Rouge2: 0.2624
- Rougel: 0.4409
- Rougelsum: 0.4427
- Bleu1: 43.8834
- Bleu2: 24.8997
- Bleu3: 17.7287
- Bleu: 22.3666
- Moverscore: 0.0510
- Cosine Distance: 0.4047
- Jaccard Similarity: 0.2798
- L1 Distance: 72.1289
- L2 Distance: 8.9081
- Freshman Readability: 12.9088

## 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-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu1   | Bleu2   | Bleu3   | Bleu    | Moverscore | Cosine Distance | Jaccard Similarity | L1 Distance | L2 Distance | Freshman Readability |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|:-------:|:-------:|:-------:|:----------:|:---------------:|:------------------:|:-----------:|:-----------:|:--------------------:|
| No log        | 1.0    | 112  | 1.6232          | 0.4393 | 0.2266 | 0.4064 | 0.4082    | 41.1287 | 21.6852 | 14.7151 | 19.1573 | 0.0221     | 0.4361          | 0.2462             | 78.5859     | 9.3605      | 11.1333              |
| No log        | 2.0    | 224  | 1.6413          | 0.4519 | 0.2467 | 0.4322 | 0.4336    | 42.7056 | 23.3160 | 16.0230 | 20.6104 | 0.0356     | 0.4215          | 0.2666             | 75.7734     | 9.1753      | 12.5991              |
| No log        | 2.9765 | 333  | 1.6590          | 0.4578 | 0.2522 | 0.4370 | 0.4382    | 43.3439 | 23.9543 | 16.4120 | 21.0878 | 0.0413     | 0.4147          | 0.2723             | 73.9766     | 9.0579      | 12.6140              |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.7.0+cu118
- Datasets 3.6.0
- Tokenizers 0.21.1