File size: 2,304 Bytes
f535954 d5183eb 04687ec 7483787 d5183eb 7483787 04687ec 7483787 f535954 d5183eb f535954 d5183eb f535954 04687ec d5183eb 04687ec f535954 d5183eb f535954 d5183eb f535954 d5183eb f535954 d5183eb f535954 d5183eb f535954 d5183eb f535954 d5183eb f535954 d5183eb f535954 d5183eb 04687ec d5183eb 04687ec d5183eb f535954 d5183eb f535954 d5183eb 04687ec f535954 d5183eb f535954 d5183eb |
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 |
---
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: w2v2-bert-urdu
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ur
split: test[:100]
args: ur
metrics:
- type: wer
value: 0.3300546448087432
name: Wer
---
<!-- 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. -->
# w2v2-bert-urdu
This model was trained from scratch on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4246
- Wer: 0.3301
## 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: 5e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 100
- num_epochs: 2
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.8145 | 0.1695 | 50 | 0.4620 | 0.3421 |
| 0.4364 | 0.3390 | 100 | 0.3969 | 0.2874 |
| 0.418 | 0.5085 | 150 | 0.3697 | 0.2820 |
| 0.402 | 0.6780 | 200 | 0.3627 | 0.2842 |
| 0.3698 | 0.8475 | 250 | 0.3314 | 0.2710 |
| 0.3779 | 1.0169 | 300 | 0.3292 | 0.2852 |
| 0.3167 | 1.1864 | 350 | 0.3230 | 0.2820 |
| 0.3578 | 1.3559 | 400 | 0.3825 | 0.2940 |
| 0.4189 | 1.5254 | 450 | 0.4225 | 0.3104 |
| 0.4803 | 1.6949 | 500 | 0.4248 | 0.3311 |
| 0.4612 | 1.8644 | 550 | 0.4246 | 0.3301 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|