---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: mms_severity_classifier
  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. -->

# mms_severity_classifier

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0834
- Accuracy: 0.9787
- F1 Macro: 0.9750
- F1 Weighted: 0.9786
- F1 Mild: 0.9581
- F1 Moderate: 0.9812
- F1 Normal: 0.9719
- F1 Severe: 0.9886

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch_fused with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Macro | F1 Weighted | F1 Mild | F1 Moderate | F1 Normal | F1 Severe |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:-----------:|:-------:|:-----------:|:---------:|:---------:|
| 0.3997        | 1.0   | 1210  | 0.3725          | 0.8652   | 0.8510   | 0.8637      | 0.7821  | 0.8791      | 0.8618    | 0.8809    |
| 0.1947        | 2.0   | 2420  | 0.2191          | 0.9193   | 0.9067   | 0.9195      | 0.8594  | 0.9330      | 0.8828    | 0.9517    |
| 0.1382        | 3.0   | 3630  | 0.1758          | 0.9433   | 0.9336   | 0.9432      | 0.8950  | 0.9519      | 0.9185    | 0.9690    |
| 0.1204        | 4.0   | 4840  | 0.1432          | 0.9573   | 0.9517   | 0.9575      | 0.9365  | 0.9653      | 0.9324    | 0.9726    |
| 0.0815        | 5.0   | 6050  | 0.0922          | 0.9726   | 0.9699   | 0.9727      | 0.9639  | 0.9748      | 0.9567    | 0.9841    |
| 0.0647        | 6.0   | 7260  | 0.0896          | 0.9753   | 0.9710   | 0.9753      | 0.9561  | 0.9819      | 0.9632    | 0.9829    |
| 0.0864        | 7.0   | 8470  | 0.1191          | 0.9726   | 0.9699   | 0.9726      | 0.9581  | 0.9734      | 0.9652    | 0.9829    |
| 0.0243        | 8.0   | 9680  | 0.0870          | 0.9787   | 0.9776   | 0.9787      | 0.9821  | 0.9810      | 0.9635    | 0.9840    |
| 0.0455        | 9.0   | 10890 | 0.0909          | 0.9760   | 0.9715   | 0.9759      | 0.9501  | 0.9795      | 0.9701    | 0.9863    |
| 0.0452        | 10.0  | 12100 | 0.0834          | 0.9787   | 0.9750   | 0.9786      | 0.9581  | 0.9812      | 0.9719    | 0.9886    |


### Framework versions

- Transformers 4.57.6
- Pytorch 2.8.0+cu128
- Datasets 4.5.0
- Tokenizers 0.22.2