File size: 3,925 Bytes
bc1a2c8 610f0e7 bc1a2c8 83b0916 bc1a2c8 |
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 |
---
license: apache-2.0
tags:
- generated_from_trainer
- pt
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_7_0
model-index:
- name: sew-tiny-portuguese-cv8
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. -->
# sew-tiny-portuguese-cv8
This model is a fine-tuned version of [lgris/sew-tiny-pt](https://huggingface.co/lgris/sew-tiny-pt) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4082
- Wer: 0.3053
## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 40000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| No log | 1.93 | 1000 | 2.9134 | 0.9767 |
| 2.9224 | 3.86 | 2000 | 2.8405 | 0.9789 |
| 2.9224 | 5.79 | 3000 | 2.8094 | 0.9800 |
| 2.8531 | 7.72 | 4000 | 2.7439 | 0.9891 |
| 2.8531 | 9.65 | 5000 | 2.7057 | 1.0159 |
| 2.7721 | 11.58 | 6000 | 2.7235 | 1.0709 |
| 2.7721 | 13.51 | 7000 | 2.5931 | 1.1035 |
| 2.6566 | 15.44 | 8000 | 2.2171 | 0.9884 |
| 2.6566 | 17.37 | 9000 | 1.2399 | 0.8081 |
| 1.9558 | 19.31 | 10000 | 0.9045 | 0.6353 |
| 1.9558 | 21.24 | 11000 | 0.7705 | 0.5533 |
| 1.4987 | 23.17 | 12000 | 0.7068 | 0.5165 |
| 1.4987 | 25.1 | 13000 | 0.6641 | 0.4718 |
| 1.3811 | 27.03 | 14000 | 0.6043 | 0.4470 |
| 1.3811 | 28.96 | 15000 | 0.5532 | 0.4268 |
| 1.2897 | 30.89 | 16000 | 0.5371 | 0.4101 |
| 1.2897 | 32.82 | 17000 | 0.5924 | 0.4150 |
| 1.225 | 34.75 | 18000 | 0.4949 | 0.3894 |
| 1.225 | 36.68 | 19000 | 0.5591 | 0.4045 |
| 1.193 | 38.61 | 20000 | 0.4927 | 0.3731 |
| 1.193 | 40.54 | 21000 | 0.4922 | 0.3712 |
| 1.1482 | 42.47 | 22000 | 0.4799 | 0.3662 |
| 1.1482 | 44.4 | 23000 | 0.4846 | 0.3648 |
| 1.1201 | 46.33 | 24000 | 0.4770 | 0.3623 |
| 1.1201 | 48.26 | 25000 | 0.4530 | 0.3426 |
| 1.0892 | 50.19 | 26000 | 0.4523 | 0.3527 |
| 1.0892 | 52.12 | 27000 | 0.4573 | 0.3443 |
| 1.0583 | 54.05 | 28000 | 0.4488 | 0.3353 |
| 1.0583 | 55.98 | 29000 | 0.4295 | 0.3285 |
| 1.0319 | 57.92 | 30000 | 0.4321 | 0.3220 |
| 1.0319 | 59.85 | 31000 | 0.4244 | 0.3236 |
| 1.0076 | 61.78 | 32000 | 0.4197 | 0.3201 |
| 1.0076 | 63.71 | 33000 | 0.4230 | 0.3208 |
| 0.9851 | 65.64 | 34000 | 0.4090 | 0.3127 |
| 0.9851 | 67.57 | 35000 | 0.4088 | 0.3133 |
| 0.9695 | 69.5 | 36000 | 0.4123 | 0.3088 |
| 0.9695 | 71.43 | 37000 | 0.4017 | 0.3090 |
| 0.9514 | 73.36 | 38000 | 0.4184 | 0.3086 |
| 0.9514 | 75.29 | 39000 | 0.4075 | 0.3043 |
| 0.944 | 77.22 | 40000 | 0.4082 | 0.3053 |
### Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0
|