---
license: apache-2.0
base_model: mHossain/ml_sum_v1
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: ml_sum_v2
  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. -->

# ml_sum_v2

This model is a fine-tuned version of [mHossain/ml_sum_v1](https://huggingface.co/mHossain/ml_sum_v1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9401
- Rouge1: 8.1448
- Rouge2: 3.3615
- Rougel: 7.4641
- Rougelsum: 7.9361
- Gen Len: 19.0

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5000
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 312  | 2.1706          | 7.2919 | 2.8117 | 6.7418 | 7.1173    | 19.0    |
| 2.4911        | 2.0   | 625  | 2.1012          | 7.7986 | 3.0952 | 7.1505 | 7.5818    | 19.0    |
| 2.4911        | 3.0   | 937  | 2.0373          | 8.0535 | 3.2228 | 7.3877 | 7.8365    | 19.0    |
| 2.3572        | 4.0   | 1250 | 1.9865          | 8.1591 | 3.31   | 7.4577 | 7.9114    | 19.0    |
| 2.2455        | 4.99  | 1560 | 1.9401          | 8.1448 | 3.3615 | 7.4641 | 7.9361    | 19.0    |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2