---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
base_model: google/mt5-large
model-index:
- name: mt5_emotion_multi
  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. -->

# mt5_emotion_multi

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: 0.3993
- Accuracy: 0.901
- Precision: 0.9037
- Recall: 0.901
- F1: 0.9008

## 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: 8
- eval_batch_size: 8
- 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 | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 0.4   | 50   | 1.6030          | 0.405    | 0.2816    | 0.405  | 0.3089 |
| No log        | 0.8   | 100  | 1.3838          | 0.5      | 0.5244    | 0.5    | 0.3826 |
| 1.5266        | 1.2   | 150  | 1.1754          | 0.535    | 0.6592    | 0.535  | 0.4998 |
| 1.5266        | 1.6   | 200  | 1.0208          | 0.645    | 0.7211    | 0.645  | 0.6155 |
| 0.7436        | 2.0   | 250  | 0.7959          | 0.735    | 0.8247    | 0.735  | 0.7121 |
| 0.7436        | 2.4   | 300  | 0.6869          | 0.79     | 0.8289    | 0.79   | 0.7871 |
| 0.7436        | 2.8   | 350  | 0.6828          | 0.805    | 0.8335    | 0.805  | 0.7983 |
| 0.2185        | 3.2   | 400  | 1.0537          | 0.75     | 0.8211    | 0.75   | 0.7343 |
| 0.2185        | 3.6   | 450  | 0.5383          | 0.85     | 0.8587    | 0.85   | 0.8474 |
| 0.1285        | 4.0   | 500  | 0.9033          | 0.795    | 0.8512    | 0.795  | 0.7851 |
| 0.1285        | 4.4   | 550  | 1.1142          | 0.755    | 0.8272    | 0.755  | 0.7371 |
| 0.1285        | 4.8   | 600  | 1.0917          | 0.77     | 0.8302    | 0.77   | 0.7640 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2