update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,80 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
model-index:
|
| 6 |
+
- name: run1
|
| 7 |
+
results: []
|
| 8 |
+
---
|
| 9 |
+
|
| 10 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 11 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 12 |
+
|
| 13 |
+
# run1
|
| 14 |
+
|
| 15 |
+
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset.
|
| 16 |
+
It achieves the following results on the evaluation set:
|
| 17 |
+
- Loss: 1.6666
|
| 18 |
+
- Wer: 0.6375
|
| 19 |
+
- Cer: 0.3170
|
| 20 |
+
|
| 21 |
+
## Model description
|
| 22 |
+
|
| 23 |
+
More information needed
|
| 24 |
+
|
| 25 |
+
## Intended uses & limitations
|
| 26 |
+
|
| 27 |
+
More information needed
|
| 28 |
+
|
| 29 |
+
## Training and evaluation data
|
| 30 |
+
|
| 31 |
+
More information needed
|
| 32 |
+
|
| 33 |
+
## Training procedure
|
| 34 |
+
|
| 35 |
+
### Training hyperparameters
|
| 36 |
+
|
| 37 |
+
The following hyperparameters were used during training:
|
| 38 |
+
- learning_rate: 0.0001
|
| 39 |
+
- train_batch_size: 8
|
| 40 |
+
- eval_batch_size: 8
|
| 41 |
+
- seed: 42
|
| 42 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 43 |
+
- lr_scheduler_type: linear
|
| 44 |
+
- lr_scheduler_warmup_steps: 2000
|
| 45 |
+
- num_epochs: 50
|
| 46 |
+
- mixed_precision_training: Native AMP
|
| 47 |
+
|
| 48 |
+
### Training results
|
| 49 |
+
|
| 50 |
+
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|
| 51 |
+
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
|
| 52 |
+
| 1.0564 | 2.36 | 2000 | 2.3456 | 0.9628 | 0.5549 |
|
| 53 |
+
| 0.5071 | 4.73 | 4000 | 2.0652 | 0.9071 | 0.5115 |
|
| 54 |
+
| 0.3952 | 7.09 | 6000 | 2.3649 | 0.9108 | 0.4628 |
|
| 55 |
+
| 0.3367 | 9.46 | 8000 | 1.7615 | 0.8253 | 0.4348 |
|
| 56 |
+
| 0.2765 | 11.82 | 10000 | 1.6151 | 0.7937 | 0.4087 |
|
| 57 |
+
| 0.2493 | 14.18 | 12000 | 1.4976 | 0.7881 | 0.3905 |
|
| 58 |
+
| 0.2318 | 16.55 | 14000 | 1.6731 | 0.8160 | 0.3925 |
|
| 59 |
+
| 0.2074 | 18.91 | 16000 | 1.5822 | 0.7658 | 0.3913 |
|
| 60 |
+
| 0.1825 | 21.28 | 18000 | 1.5442 | 0.7361 | 0.3704 |
|
| 61 |
+
| 0.1824 | 23.64 | 20000 | 1.5988 | 0.7621 | 0.3711 |
|
| 62 |
+
| 0.1699 | 26.0 | 22000 | 1.4261 | 0.7119 | 0.3490 |
|
| 63 |
+
| 0.158 | 28.37 | 24000 | 1.7482 | 0.7658 | 0.3648 |
|
| 64 |
+
| 0.1385 | 30.73 | 26000 | 1.4103 | 0.6784 | 0.3348 |
|
| 65 |
+
| 0.1199 | 33.1 | 28000 | 1.5214 | 0.6636 | 0.3273 |
|
| 66 |
+
| 0.116 | 35.46 | 30000 | 1.4288 | 0.7212 | 0.3486 |
|
| 67 |
+
| 0.1071 | 37.83 | 32000 | 1.5344 | 0.7138 | 0.3411 |
|
| 68 |
+
| 0.1007 | 40.19 | 34000 | 1.4501 | 0.6691 | 0.3237 |
|
| 69 |
+
| 0.0943 | 42.55 | 36000 | 1.5367 | 0.6859 | 0.3265 |
|
| 70 |
+
| 0.0844 | 44.92 | 38000 | 1.5321 | 0.6599 | 0.3273 |
|
| 71 |
+
| 0.0762 | 47.28 | 40000 | 1.6721 | 0.6264 | 0.3142 |
|
| 72 |
+
| 0.0778 | 49.65 | 42000 | 1.6666 | 0.6375 | 0.3170 |
|
| 73 |
+
|
| 74 |
+
|
| 75 |
+
### Framework versions
|
| 76 |
+
|
| 77 |
+
- Transformers 4.18.0
|
| 78 |
+
- Pytorch 1.12.0+cu113
|
| 79 |
+
- Datasets 2.0.0
|
| 80 |
+
- Tokenizers 0.12.1
|