transformers tensorboard safetensors mt5 text2text-generation generated_from_trainer base_model:Buseak/md_mt5_base_boun_split_second_v1_retrain_on_second_imst license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: Buseak/md_mt5_base_boun_split_second_v1_retrain_on_second_imst
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: md_mt5_base_boun_split_second_v1_retrain_on_boun_1612
  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. -->

# md_mt5_base_boun_split_second_v1_retrain_on_boun_1612

This model is a fine-tuned version of [Buseak/md_mt5_base_boun_split_second_v1_retrain_on_second_imst](https://huggingface.co/Buseak/md_mt5_base_boun_split_second_v1_retrain_on_second_imst) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1146
- Bleu: 0.7971
- Gen Len: 18.8069

## 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: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Bleu   | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|
| 0.3542        | 1.0   | 975   | 0.1679          | 0.7453 | 18.7959 |
| 0.3354        | 2.0   | 1950  | 0.1553          | 0.7492 | 18.8033 |
| 0.3183        | 3.0   | 2925  | 0.1500          | 0.7576 | 18.7972 |
| 0.3013        | 4.0   | 3900  | 0.1421          | 0.7618 | 18.7969 |
| 0.2912        | 5.0   | 4875  | 0.1364          | 0.7673 | 18.8005 |
| 0.2816        | 6.0   | 5850  | 0.1321          | 0.7732 | 18.8003 |
| 0.2753        | 7.0   | 6825  | 0.1287          | 0.7825 | 18.8067 |
| 0.2718        | 8.0   | 7800  | 0.1252          | 0.7866 | 18.8051 |
| 0.2631        | 9.0   | 8775  | 0.1222          | 0.7885 | 18.799  |
| 0.2576        | 10.0  | 9750  | 0.1197          | 0.793  | 18.8041 |
| 0.2541        | 11.0  | 10725 | 0.1182          | 0.7935 | 18.8056 |
| 0.2505        | 12.0  | 11700 | 0.1165          | 0.7956 | 18.8056 |
| 0.2492        | 13.0  | 12675 | 0.1156          | 0.7971 | 18.8056 |
| 0.2534        | 14.0  | 13650 | 0.1146          | 0.7964 | 18.8069 |
| 0.2455        | 15.0  | 14625 | 0.1146          | 0.7971 | 18.8069 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
