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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
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