fine tuneing with add. datasets (magic-data, fleurs)
Browse files- README.md +22 -19
- all_results.json +10 -10
- config.json +2 -2
- eval_results.json +6 -6
- pytorch_model.bin +1 -1
- runs/Dec18_23-09-53_4848315c9cd8/1671407022.448812/events.out.tfevents.1671407022.4848315c9cd8.23187.1 +3 -0
- runs/Dec18_23-09-53_4848315c9cd8/events.out.tfevents.1671407022.4848315c9cd8.23187.0 +3 -0
- runs/Dec18_23-09-53_4848315c9cd8/events.out.tfevents.1671502298.4848315c9cd8.23187.2 +3 -0
- tokenizer_config.json +1 -1
- train_results.json +5 -5
- trainer_state.json +1888 -643
- 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: 6.
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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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# Whisper Large Indonesian
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This model is a fine-tuned version of [openai/whisper-large
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 6.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-
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- train_batch_size:
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- eval_batch_size:
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 64
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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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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: 6.248270773771097
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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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# Whisper Large Indonesian
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This model is a fine-tuned version of [openai/whisper-large](https://huggingface.co/openai/whisper-large) on the mozilla-foundation/common_voice_11_0, magic_data, titml id dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.2034
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- Wer: 6.2483
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-06
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- train_batch_size: 12
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- eval_batch_size: 12
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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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| 0.1516 | 0.5 | 1000 | 0.1730 | 6.5664 |
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| 0.1081 | 1.0 | 2000 | 0.1638 | 6.3682 |
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| 0.0715 | 1.49 | 3000 | 0.1803 | 6.2713 |
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| 0.1009 | 1.99 | 4000 | 0.1796 | 6.2667 |
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| 0.0387 | 2.49 | 5000 | 0.2054 | 6.4927 |
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| 0.0494 | 2.99 | 6000 | 0.2034 | 6.2483 |
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| 0.0259 | 3.48 | 7000 | 0.2226 | 6.3497 |
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| 0.0265 | 3.98 | 8000 | 0.2274 | 6.4004 |
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| 0.0232 | 4.48 | 9000 | 0.2443 | 6.5618 |
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| 0.015 | 4.98 | 10000 | 0.2413 | 6.4927 |
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### Framework versions
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all_results.json
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config.json
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| 1225 |
-
"loss": 0.
|
| 1226 |
"step": 4925
|
| 1227 |
},
|
| 1228 |
{
|
| 1229 |
-
"epoch":
|
| 1230 |
-
"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": 49
|
| 1242 |
-
"learning_rate":
|
| 1243 |
-
"loss": 0.
|
| 1244 |
"step": 5000
|
| 1245 |
},
|
| 1246 |
{
|
| 1247 |
-
"epoch": 49
|
| 1248 |
-
"eval_loss": 0.
|
| 1249 |
-
"eval_runtime":
|
| 1250 |
-
"eval_samples_per_second":
|
| 1251 |
-
"eval_steps_per_second": 0.
|
| 1252 |
-
"eval_wer": 6.
|
| 1253 |
"step": 5000
|
| 1254 |
},
|
| 1255 |
{
|
| 1256 |
-
"epoch":
|
| 1257 |
-
"
|
| 1258 |
-
"
|
| 1259 |
-
"
|
| 1260 |
-
|
| 1261 |
-
|
| 1262 |
-
"
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