---
library_name: transformers
license: cc-by-nc-4.0
base_model: mms-meta/mms-zeroshot-300m
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-zeroshot-300m-genbed-f-model
  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-zeroshot-300m-genbed-f-model

This model is a fine-tuned version of [mms-meta/mms-zeroshot-300m](https://huggingface.co/mms-meta/mms-zeroshot-300m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2131
- Wer: 0.3720

## 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: 0.0003
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| No log        | 0.5479  | 200  | 2.3236          | 1.0    |
| No log        | 1.0959  | 400  | 0.3331          | 0.5504 |
| 2.6731        | 1.6438  | 600  | 0.2969          | 0.5190 |
| 2.6731        | 2.1918  | 800  | 0.2806          | 0.5122 |
| 0.4193        | 2.7397  | 1000 | 0.2701          | 0.4742 |
| 0.4193        | 3.2877  | 1200 | 0.2703          | 0.4770 |
| 0.4193        | 3.8356  | 1400 | 0.2574          | 0.4758 |
| 0.367         | 4.3836  | 1600 | 0.2487          | 0.4547 |
| 0.367         | 4.9315  | 1800 | 0.2472          | 0.4337 |
| 0.3377        | 5.4795  | 2000 | 0.2424          | 0.4467 |
| 0.3377        | 6.0274  | 2200 | 0.2372          | 0.4274 |
| 0.3377        | 6.5753  | 2400 | 0.2366          | 0.4225 |
| 0.3282        | 7.1233  | 2600 | 0.2339          | 0.4104 |
| 0.3282        | 7.6712  | 2800 | 0.2352          | 0.4193 |
| 0.3018        | 8.2192  | 3000 | 0.2249          | 0.4097 |
| 0.3018        | 8.7671  | 3200 | 0.2254          | 0.4065 |
| 0.3018        | 9.3151  | 3400 | 0.2251          | 0.4021 |
| 0.2945        | 9.8630  | 3600 | 0.2248          | 0.3969 |
| 0.2945        | 10.4110 | 3800 | 0.2212          | 0.4002 |
| 0.2843        | 10.9589 | 4000 | 0.2200          | 0.3920 |
| 0.2843        | 11.5068 | 4200 | 0.2183          | 0.3853 |
| 0.2843        | 12.0548 | 4400 | 0.2174          | 0.3890 |
| 0.2755        | 12.6027 | 4600 | 0.2163          | 0.3955 |
| 0.2755        | 13.1507 | 4800 | 0.2197          | 0.3894 |
| 0.2699        | 13.6986 | 5000 | 0.2163          | 0.3899 |
| 0.2699        | 14.2466 | 5200 | 0.2129          | 0.3769 |
| 0.2699        | 14.7945 | 5400 | 0.2114          | 0.3759 |
| 0.2568        | 15.3425 | 5600 | 0.2100          | 0.3721 |
| 0.2568        | 15.8904 | 5800 | 0.2140          | 0.3670 |
| 0.2521        | 16.4384 | 6000 | 0.2149          | 0.3743 |
| 0.2521        | 16.9863 | 6200 | 0.2131          | 0.3720 |


### Framework versions

- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0