fine tuned on other datasets
Browse files- README.md +22 -18
- all_results.json +10 -10
- config.json +2 -2
- eval_results.json +6 -6
- pytorch_model.bin +1 -1
- runs/Dec18_13-03-49_4848315c9cd8/1671378327.9603035/events.out.tfevents.1671378327.4848315c9cd8.59162.1 +3 -0
- runs/Dec18_13-03-49_4848315c9cd8/events.out.tfevents.1671378327.4848315c9cd8.59162.0 +3 -0
- runs/Dec18_13-03-49_4848315c9cd8/events.out.tfevents.1671392456.4848315c9cd8.59162.2 +3 -0
- tokenizer_config.json +1 -1
- train_results.json +5 -5
- trainer_state.json +1889 -644
- training_args.bin +1 -1
README.md
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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metrics:
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- wer
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model-index:
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type: mozilla-foundation/common_voice_11_0
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config: id
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split: test
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args: id
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metrics:
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- name: Wer
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type: wer
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value:
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Whisper Tiny Indonesian
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps:
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step
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### Framework versions
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- generated_from_trainer
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datasets:
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- mozilla-foundation/common_voice_11_0
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- magic_data
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- titml
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- google/fleurs
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metrics:
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- wer
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model-index:
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type: mozilla-foundation/common_voice_11_0
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config: id
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split: test
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metrics:
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- name: Wer
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type: wer
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value: 18.28368532693904
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---
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# Whisper Tiny Indonesian
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This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the mozilla-foundation/common_voice_11_0, magic_data, titml and google/fleurs dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2409
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- Wer: 18.2837
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 16
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 500
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- training_steps: 10000
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|
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| 0.4103 | 0.66 | 1000 | 0.3802 | 27.0497 |
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| 0.2682 | 1.32 | 2000 | 0.3223 | 22.9365 |
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| 0.2381 | 1.99 | 3000 | 0.2884 | 20.8245 |
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| 0.1606 | 2.65 | 4000 | 0.2727 | 20.1928 |
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| 0.1246 | 3.31 | 5000 | 0.2596 | 18.9984 |
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| 0.1344 | 3.97 | 6000 | 0.2482 | 18.7540 |
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| 0.0975 | 4.63 | 7000 | 0.2471 | 18.6388 |
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| 0.0916 | 5.29 | 8000 | 0.2436 | 18.9615 |
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| 0.0854 | 5.96 | 9000 | 0.2413 | 18.3114 |
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| 0.0812 | 6.62 | 10000 | 0.2409 | 18.2837 |
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### Framework versions
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all_results.json
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config.json
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"learning_rate":
|
| 1231 |
-
"loss": 0.
|
| 1232 |
"step": 4950
|
| 1233 |
},
|
| 1234 |
{
|
| 1235 |
-
"epoch":
|
| 1236 |
-
"learning_rate":
|
| 1237 |
-
"loss": 0.
|
| 1238 |
"step": 4975
|
| 1239 |
},
|
| 1240 |
{
|
| 1241 |
-
"epoch":
|
| 1242 |
-
"learning_rate":
|
| 1243 |
-
"loss": 0.
|
| 1244 |
"step": 5000
|
| 1245 |
},
|
| 1246 |
{
|
| 1247 |
-
"epoch":
|
| 1248 |
-
"eval_loss": 0.
|
| 1249 |
-
"eval_runtime":
|
| 1250 |
-
"eval_samples_per_second":
|
| 1251 |
-
"eval_steps_per_second": 0.
|
| 1252 |
-
"eval_wer":
|
| 1253 |
"step": 5000
|
| 1254 |
},
|
| 1255 |
{
|
| 1256 |
-
"epoch":
|
| 1257 |
-
"
|
| 1258 |
-
"
|
| 1259 |
-
"
|
| 1260 |
-
|
| 1261 |
-
|
| 1262 |
-
"
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