---
license: apache-2.0
tags:
- generated_from_trainer
base_model: google/mt5-large
metrics:
- rouge
- bleu
model-index:
- name: TURNA_TSATweets_cond_gen_no_instruction
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# TURNA_TSATweets_cond_gen_no_instruction

This model is a fine-tuned version of [google/mt5-large](https://huggingface.co/google/mt5-large) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0710
- Rouge1: 0.708
- Rouge2: 0.094
- Rougel: 0.709
- Rougelsum: 0.708
- Bleu: 0.0
- Precisions: [0.709, 0.0, 0.0, 0.0]
- Brevity Penalty: 1.0
- Length Ratio: 1.0
- Translation Length: 1000
- Reference Length: 1000
- Meteor: 0.3545
- Score: 29.1000
- Num Edits: 291
- Ref Length: 1000.0

## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Bleu | Precisions                          | Brevity Penalty | Length Ratio | Translation Length | Reference Length | Meteor | Score   | Num Edits | Ref Length |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:----:|:-----------------------------------:|:---------------:|:------------:|:------------------:|:----------------:|:------:|:-------:|:---------:|:----------:|
| No log        | 0.5   | 82   | 0.1335          | 0.2707 | 0.0    | 0.2707 | 0.2707    | 0.0  | [0.2706896551724138, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.1353 | 72.9310 | 423       | 580.0      |
| 2.9168        | 1.0   | 164  | 0.0903          | 0.6172 | 0.0017 | 0.6190 | 0.6155    | 0.0  | [0.6172413793103448, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3086 | 38.2759 | 222       | 580.0      |
| 2.9168        | 1.5   | 246  | 0.0968          | 0.6310 | 0.0    | 0.6328 | 0.6310    | 0.0  | [0.6310344827586207, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3155 | 36.8966 | 214       | 580.0      |
| 0.1116        | 2.0   | 328  | 0.0769          | 0.6586 | 0.0328 | 0.6603 | 0.6603    | 0.0  | [0.6603448275862069, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3302 | 33.9655 | 197       | 580.0      |
| 0.1116        | 2.5   | 410  | 0.0762          | 0.6931 | 0.0707 | 0.6931 | 0.6931    | 0.0  | [0.6931034482758621, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3466 | 30.6897 | 178       | 580.0      |
| 0.0921        | 3.0   | 492  | 0.0709          | 0.6931 | 0.0276 | 0.6931 | 0.6931    | 0.0  | [0.6931034482758621, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3466 | 30.6897 | 178       | 580.0      |
| 0.0921        | 3.5   | 574  | 0.0897          | 0.6897 | 0.0379 | 0.6897 | 0.6897    | 0.0  | [0.6896551724137931, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3448 | 31.0345 | 180       | 580.0      |
| 0.079         | 4.0   | 656  | 0.0679          | 0.6931 | 0.0707 | 0.6948 | 0.6931    | 0.0  | [0.6948275862068966, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3474 | 30.5172 | 177       | 580.0      |
| 0.079         | 4.5   | 738  | 0.0771          | 0.7103 | 0.0345 | 0.7103 | 0.7103    | 0.0  | [0.7103448275862069, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3552 | 28.9655 | 168       | 580.0      |
| 0.0712        | 5.0   | 820  | 0.0675          | 0.7043 | 0.0517 | 0.7034 | 0.7034    | 0.0  | [0.7051724137931035, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3526 | 29.4828 | 171       | 580.0      |
| 0.0712        | 5.5   | 902  | 0.0657          | 0.7138 | 0.0603 | 0.7138 | 0.7138    | 0.0  | [0.7137931034482758, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3569 | 28.6207 | 166       | 580.0      |
| 0.065         | 6.0   | 984  | 0.0670          | 0.7052 | 0.0621 | 0.7069 | 0.7069    | 0.0  | [0.7068965517241379, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3534 | 29.3103 | 170       | 580.0      |
| 0.065         | 6.5   | 1066 | 0.0658          | 0.7086 | 0.0672 | 0.7103 | 0.7086    | 0.0  | [0.7103448275862069, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3552 | 28.9655 | 168       | 580.0      |
| 0.0596        | 7.0   | 1148 | 0.0741          | 0.7138 | 0.0586 | 0.7155 | 0.7155    | 0.0  | [0.7155172413793104, 0.0, 0.0, 0.0] | 1.0             | 1.0          | 580                | 580              | 0.3578 | 28.4483 | 165       | 580.0      |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1