update model card README.md
Browse files
README.md
ADDED
@@ -0,0 +1,102 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
---
|
2 |
+
license: apache-2.0
|
3 |
+
tags:
|
4 |
+
- generated_from_trainer
|
5 |
+
datasets:
|
6 |
+
- common_voice
|
7 |
+
model-index:
|
8 |
+
- name: sew-tiny-portuguese-cv8
|
9 |
+
results: []
|
10 |
+
---
|
11 |
+
|
12 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
13 |
+
should probably proofread and complete it, then remove this comment. -->
|
14 |
+
|
15 |
+
# sew-tiny-portuguese-cv8
|
16 |
+
|
17 |
+
This model is a fine-tuned version of [lgris/sew-tiny-pt](https://huggingface.co/lgris/sew-tiny-pt) on the common_voice dataset.
|
18 |
+
It achieves the following results on the evaluation set:
|
19 |
+
- Loss: 0.4082
|
20 |
+
- Wer: 0.3053
|
21 |
+
|
22 |
+
## Model description
|
23 |
+
|
24 |
+
More information needed
|
25 |
+
|
26 |
+
## Intended uses & limitations
|
27 |
+
|
28 |
+
More information needed
|
29 |
+
|
30 |
+
## Training and evaluation data
|
31 |
+
|
32 |
+
More information needed
|
33 |
+
|
34 |
+
## Training procedure
|
35 |
+
|
36 |
+
### Training hyperparameters
|
37 |
+
|
38 |
+
The following hyperparameters were used during training:
|
39 |
+
- learning_rate: 0.0001
|
40 |
+
- train_batch_size: 8
|
41 |
+
- eval_batch_size: 8
|
42 |
+
- seed: 42
|
43 |
+
- gradient_accumulation_steps: 4
|
44 |
+
- total_train_batch_size: 32
|
45 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
46 |
+
- lr_scheduler_type: linear
|
47 |
+
- lr_scheduler_warmup_steps: 1000
|
48 |
+
- training_steps: 40000
|
49 |
+
- mixed_precision_training: Native AMP
|
50 |
+
|
51 |
+
### Training results
|
52 |
+
|
53 |
+
| Training Loss | Epoch | Step | Validation Loss | Wer |
|
54 |
+
|:-------------:|:-----:|:-----:|:---------------:|:------:|
|
55 |
+
| No log | 1.93 | 1000 | 2.9134 | 0.9767 |
|
56 |
+
| 2.9224 | 3.86 | 2000 | 2.8405 | 0.9789 |
|
57 |
+
| 2.9224 | 5.79 | 3000 | 2.8094 | 0.9800 |
|
58 |
+
| 2.8531 | 7.72 | 4000 | 2.7439 | 0.9891 |
|
59 |
+
| 2.8531 | 9.65 | 5000 | 2.7057 | 1.0159 |
|
60 |
+
| 2.7721 | 11.58 | 6000 | 2.7235 | 1.0709 |
|
61 |
+
| 2.7721 | 13.51 | 7000 | 2.5931 | 1.1035 |
|
62 |
+
| 2.6566 | 15.44 | 8000 | 2.2171 | 0.9884 |
|
63 |
+
| 2.6566 | 17.37 | 9000 | 1.2399 | 0.8081 |
|
64 |
+
| 1.9558 | 19.31 | 10000 | 0.9045 | 0.6353 |
|
65 |
+
| 1.9558 | 21.24 | 11000 | 0.7705 | 0.5533 |
|
66 |
+
| 1.4987 | 23.17 | 12000 | 0.7068 | 0.5165 |
|
67 |
+
| 1.4987 | 25.1 | 13000 | 0.6641 | 0.4718 |
|
68 |
+
| 1.3811 | 27.03 | 14000 | 0.6043 | 0.4470 |
|
69 |
+
| 1.3811 | 28.96 | 15000 | 0.5532 | 0.4268 |
|
70 |
+
| 1.2897 | 30.89 | 16000 | 0.5371 | 0.4101 |
|
71 |
+
| 1.2897 | 32.82 | 17000 | 0.5924 | 0.4150 |
|
72 |
+
| 1.225 | 34.75 | 18000 | 0.4949 | 0.3894 |
|
73 |
+
| 1.225 | 36.68 | 19000 | 0.5591 | 0.4045 |
|
74 |
+
| 1.193 | 38.61 | 20000 | 0.4927 | 0.3731 |
|
75 |
+
| 1.193 | 40.54 | 21000 | 0.4922 | 0.3712 |
|
76 |
+
| 1.1482 | 42.47 | 22000 | 0.4799 | 0.3662 |
|
77 |
+
| 1.1482 | 44.4 | 23000 | 0.4846 | 0.3648 |
|
78 |
+
| 1.1201 | 46.33 | 24000 | 0.4770 | 0.3623 |
|
79 |
+
| 1.1201 | 48.26 | 25000 | 0.4530 | 0.3426 |
|
80 |
+
| 1.0892 | 50.19 | 26000 | 0.4523 | 0.3527 |
|
81 |
+
| 1.0892 | 52.12 | 27000 | 0.4573 | 0.3443 |
|
82 |
+
| 1.0583 | 54.05 | 28000 | 0.4488 | 0.3353 |
|
83 |
+
| 1.0583 | 55.98 | 29000 | 0.4295 | 0.3285 |
|
84 |
+
| 1.0319 | 57.92 | 30000 | 0.4321 | 0.3220 |
|
85 |
+
| 1.0319 | 59.85 | 31000 | 0.4244 | 0.3236 |
|
86 |
+
| 1.0076 | 61.78 | 32000 | 0.4197 | 0.3201 |
|
87 |
+
| 1.0076 | 63.71 | 33000 | 0.4230 | 0.3208 |
|
88 |
+
| 0.9851 | 65.64 | 34000 | 0.4090 | 0.3127 |
|
89 |
+
| 0.9851 | 67.57 | 35000 | 0.4088 | 0.3133 |
|
90 |
+
| 0.9695 | 69.5 | 36000 | 0.4123 | 0.3088 |
|
91 |
+
| 0.9695 | 71.43 | 37000 | 0.4017 | 0.3090 |
|
92 |
+
| 0.9514 | 73.36 | 38000 | 0.4184 | 0.3086 |
|
93 |
+
| 0.9514 | 75.29 | 39000 | 0.4075 | 0.3043 |
|
94 |
+
| 0.944 | 77.22 | 40000 | 0.4082 | 0.3053 |
|
95 |
+
|
96 |
+
|
97 |
+
### Framework versions
|
98 |
+
|
99 |
+
- Transformers 4.16.0.dev0
|
100 |
+
- Pytorch 1.10.1+cu102
|
101 |
+
- Datasets 1.17.1.dev0
|
102 |
+
- Tokenizers 0.11.0
|