transformers tensorboard onnx safetensors mt5 text2text-generation generated_from_trainer base_model:jhpassion0621/kp-mt5-large license:apache-2.0 autotrain_compatible endpoints_compatible region:us
---
license: apache-2.0
base_model: jhpassion0621/kp-mt5-large
tags:
- generated_from_trainer
metrics:
- bleu
model-index:
- name: kp-mt5-large
  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. -->

# kp-mt5-large

This model is a fine-tuned version of [jhpassion0621/kp-mt5-large](https://huggingface.co/jhpassion0621/kp-mt5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5586
- Bleu: 43.3983
- Gen Len: 45.6585

## 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: 2.59e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step   | Bleu    | Gen Len | Validation Loss |
|:-------------:|:-----:|:------:|:-------:|:-------:|:---------------:|
| 1.0364        | 0.29  | 17000  | 32.5573 | 44.7582 | 0.8278          |
| 0.8819        | 0.58  | 34000  | 37.1161 | 45.0568 | 0.7062          |
| 0.7731        | 0.87  | 51000  | 40.329  | 45.7359 | 0.6188          |
| 0.7339        | 1.16  | 68000  | 41.7643 | 45.8618 | 0.5866          |
| 0.7093        | 1.45  | 85000  | 42.6878 | 45.5649 | 0.5657          |
| 0.6818        | 1.74  | 102000 | 43.2023 | 45.7701 | 0.5609          |
| 0.6739        | 2.00  | 117444 | 43.3983 | 45.6585 | 0.5586          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
