update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,76 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
model-index:
|
6 |
+
- name: wav2vec2-base-timit-demo-colab
|
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 |
+
# wav2vec2-base-timit-demo-colab
|
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: 2.9314
|
18 |
+
- Wer: 1.0
|
19 |
+
|
20 |
+
## Model description
|
21 |
+
|
22 |
+
More information needed
|
23 |
+
|
24 |
+
## Intended uses & limitations
|
25 |
+
|
26 |
+
More information needed
|
27 |
+
|
28 |
+
## Training and evaluation data
|
29 |
+
|
30 |
+
More information needed
|
31 |
+
|
32 |
+
## Training procedure
|
33 |
+
|
34 |
+
### Training hyperparameters
|
35 |
+
|
36 |
+
The following hyperparameters were used during training:
|
37 |
+
- learning_rate: 0.0001
|
38 |
+
- train_batch_size: 32
|
39 |
+
- eval_batch_size: 8
|
40 |
+
- seed: 42
|
41 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
42 |
+
- lr_scheduler_type: linear
|
43 |
+
- lr_scheduler_warmup_steps: 1000
|
44 |
+
- num_epochs: 3
|
45 |
+
- mixed_precision_training: Native AMP
|
46 |
+
|
47 |
+
### Training results
|
48 |
+
|
49 |
+
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
50 |
+
|:-------------:|:-----:|:----:|:---------------:|:---:|
|
51 |
+
| 8.686 | 0.16 | 20 | 13.6565 | 1.0 |
|
52 |
+
| 8.0711 | 0.32 | 40 | 12.5379 | 1.0 |
|
53 |
+
| 6.9967 | 0.48 | 60 | 9.7215 | 1.0 |
|
54 |
+
| 5.2368 | 0.64 | 80 | 5.8459 | 1.0 |
|
55 |
+
| 3.4499 | 0.8 | 100 | 3.3413 | 1.0 |
|
56 |
+
| 3.1261 | 0.96 | 120 | 3.2858 | 1.0 |
|
57 |
+
| 3.0654 | 1.12 | 140 | 3.1945 | 1.0 |
|
58 |
+
| 3.0421 | 1.28 | 160 | 3.1296 | 1.0 |
|
59 |
+
| 3.0035 | 1.44 | 180 | 3.1172 | 1.0 |
|
60 |
+
| 3.0067 | 1.6 | 200 | 3.1217 | 1.0 |
|
61 |
+
| 2.9867 | 1.76 | 220 | 3.0715 | 1.0 |
|
62 |
+
| 2.9653 | 1.92 | 240 | 3.0747 | 1.0 |
|
63 |
+
| 2.9629 | 2.08 | 260 | 2.9984 | 1.0 |
|
64 |
+
| 2.9462 | 2.24 | 280 | 2.9991 | 1.0 |
|
65 |
+
| 2.9391 | 2.4 | 300 | 3.0391 | 1.0 |
|
66 |
+
| 2.934 | 2.56 | 320 | 2.9682 | 1.0 |
|
67 |
+
| 2.9193 | 2.72 | 340 | 2.9701 | 1.0 |
|
68 |
+
| 2.8985 | 2.88 | 360 | 2.9314 | 1.0 |
|
69 |
+
|
70 |
+
|
71 |
+
### Framework versions
|
72 |
+
|
73 |
+
- Transformers 4.11.3
|
74 |
+
- Pytorch 1.10.0+cu111
|
75 |
+
- Datasets 1.13.3
|
76 |
+
- Tokenizers 0.10.3
|