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---
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
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