File size: 4,430 Bytes
1df3eff |
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 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 |
---
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: mascir_fr_hubert_version1000
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. -->
# mascir_fr_hubert_version1000
This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co./facebook/hubert-large-ls960-ft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0469
- Wer: 0.5322
## 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: 0.0001
- 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: 1000
- num_epochs: 100
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| No log | 2.0 | 250 | 3.0909 | 1.0 |
| 5.0589 | 4.0 | 500 | 2.9060 | 1.0 |
| 5.0589 | 6.0 | 750 | 1.3938 | 0.9789 |
| 1.8801 | 8.0 | 1000 | 0.9636 | 0.8422 |
| 1.8801 | 10.0 | 1250 | 0.8361 | 0.7644 |
| 0.8006 | 12.0 | 1500 | 0.8474 | 0.7444 |
| 0.8006 | 14.0 | 1750 | 0.8360 | 0.7078 |
| 0.5307 | 16.0 | 2000 | 0.8514 | 0.6944 |
| 0.5307 | 18.0 | 2250 | 0.8770 | 0.6544 |
| 0.3998 | 20.0 | 2500 | 0.8200 | 0.65 |
| 0.3998 | 22.0 | 2750 | 0.8362 | 0.63 |
| 0.3281 | 24.0 | 3000 | 0.8933 | 0.6144 |
| 0.3281 | 26.0 | 3250 | 0.9355 | 0.62 |
| 0.262 | 28.0 | 3500 | 0.9134 | 0.6222 |
| 0.262 | 30.0 | 3750 | 0.9302 | 0.5989 |
| 0.2256 | 32.0 | 4000 | 0.9307 | 0.5856 |
| 0.2256 | 34.0 | 4250 | 0.9078 | 0.6011 |
| 0.2011 | 36.0 | 4500 | 0.9647 | 0.5822 |
| 0.2011 | 38.0 | 4750 | 0.9252 | 0.5844 |
| 0.1819 | 40.0 | 5000 | 0.9917 | 0.5711 |
| 0.1819 | 42.0 | 5250 | 0.9577 | 0.5678 |
| 0.1706 | 44.0 | 5500 | 1.0094 | 0.5722 |
| 0.1706 | 46.0 | 5750 | 0.9774 | 0.5722 |
| 0.1504 | 48.0 | 6000 | 0.9702 | 0.5456 |
| 0.1504 | 50.0 | 6250 | 0.9575 | 0.5756 |
| 0.1509 | 52.0 | 6500 | 0.9855 | 0.5644 |
| 0.1509 | 54.0 | 6750 | 0.9429 | 0.5411 |
| 0.1292 | 56.0 | 7000 | 1.0471 | 0.5644 |
| 0.1292 | 58.0 | 7250 | 1.0106 | 0.5589 |
| 0.1217 | 60.0 | 7500 | 1.0118 | 0.5544 |
| 0.1217 | 62.0 | 7750 | 1.0415 | 0.5478 |
| 0.1187 | 64.0 | 8000 | 1.0047 | 0.5489 |
| 0.1187 | 66.0 | 8250 | 1.0700 | 0.5644 |
| 0.1075 | 68.0 | 8500 | 1.0357 | 0.5444 |
| 0.1075 | 70.0 | 8750 | 0.9647 | 0.5444 |
| 0.1009 | 72.0 | 9000 | 1.0392 | 0.5489 |
| 0.1009 | 74.0 | 9250 | 1.0569 | 0.5433 |
| 0.0997 | 76.0 | 9500 | 1.0266 | 0.5456 |
| 0.0997 | 78.0 | 9750 | 1.0328 | 0.54 |
| 0.101 | 80.0 | 10000 | 1.0338 | 0.5522 |
| 0.101 | 82.0 | 10250 | 1.0422 | 0.5511 |
| 0.088 | 84.0 | 10500 | 1.0233 | 0.55 |
| 0.088 | 86.0 | 10750 | 1.0446 | 0.5522 |
| 0.0922 | 88.0 | 11000 | 1.0558 | 0.5467 |
| 0.0922 | 90.0 | 11250 | 1.0405 | 0.5433 |
| 0.0863 | 92.0 | 11500 | 1.0336 | 0.5322 |
| 0.0863 | 94.0 | 11750 | 1.0575 | 0.5356 |
| 0.0845 | 96.0 | 12000 | 1.0449 | 0.5378 |
| 0.0845 | 98.0 | 12250 | 1.0482 | 0.5344 |
| 0.0818 | 100.0 | 12500 | 1.0469 | 0.5322 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.3
- Tokenizers 0.13.3
|