File size: 2,808 Bytes
fbe0289 82c0e33 fbe0289 82c0e33 fbe0289 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 |
---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- automatic-speech-recognition
- nyagen
- mms
- generated_from_trainer
metrics:
- wer
model-index:
- name: mms-1b-nyagen-male-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-1b-nyagen-male-model
This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the NYAGEN - BEM dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1298
- Wer: 0.1952
## 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: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- 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 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 6.345 | 0.2463 | 100 | 0.4506 | 0.4026 |
| 0.353 | 0.4926 | 200 | 0.2066 | 0.2924 |
| 0.2989 | 0.7389 | 300 | 0.1829 | 0.2715 |
| 0.2402 | 0.9852 | 400 | 0.1674 | 0.2546 |
| 0.2302 | 1.2315 | 500 | 0.1582 | 0.2436 |
| 0.2279 | 1.4778 | 600 | 0.1602 | 0.2428 |
| 0.2264 | 1.7241 | 700 | 0.1507 | 0.2287 |
| 0.2276 | 1.9704 | 800 | 0.1496 | 0.2353 |
| 0.2088 | 2.2167 | 900 | 0.1460 | 0.2208 |
| 0.1881 | 2.4631 | 1000 | 0.1455 | 0.2165 |
| 0.2079 | 2.7094 | 1100 | 0.1418 | 0.2168 |
| 0.196 | 2.9557 | 1200 | 0.1404 | 0.2086 |
| 0.1782 | 3.2020 | 1300 | 0.1373 | 0.2078 |
| 0.1741 | 3.4483 | 1400 | 0.1343 | 0.1944 |
| 0.1948 | 3.6946 | 1500 | 0.1318 | 0.2137 |
| 0.1904 | 3.9409 | 1600 | 0.1307 | 0.2043 |
| 0.1762 | 4.1872 | 1700 | 0.1313 | 0.2003 |
| 0.1718 | 4.4335 | 1800 | 0.1275 | 0.1932 |
| 0.1595 | 4.6798 | 1900 | 0.1276 | 0.1952 |
| 0.1811 | 4.9261 | 2000 | 0.1290 | 0.1983 |
| 0.1477 | 5.1724 | 2100 | 0.1298 | 0.1952 |
### Framework versions
- Transformers 4.48.0.dev0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
|