arslanarjumand
commited on
arslanarjumand/wav2vec-read-aloud
Browse files- README.md +15 -15
- config.json +4 -4
- model.safetensors +2 -2
- training_args.bin +1 -1
README.md
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@@ -15,11 +15,11 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Pcc Accuracy: 0.
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- Pcc Fluency: 0.
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- Pcc Total Score: 0.
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- Pcc Content:
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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:
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- train_batch_size: 2
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- eval_batch_size: 6
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- seed: 42
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- total_train_batch_size: 24
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
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### Framework versions
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1115
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- Pcc Accuracy: 0.7918
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- Pcc Fluency: 0.7940
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- Pcc Total Score: 0.8472
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- Pcc Content: 0.8160
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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: 0.00055
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- train_batch_size: 2
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- eval_batch_size: 6
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- seed: 42
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- total_train_batch_size: 24
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.25
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- num_epochs: 14
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
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|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
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| 0.1483 | 1.94 | 500 | 0.1659 | 0.7256 | 0.6982 | 0.7616 | 0.7480 |
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| 0.1338 | 3.89 | 1000 | 0.1369 | 0.7706 | 0.7680 | 0.8154 | 0.7835 |
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| 0.124 | 5.83 | 1500 | 0.1754 | 0.6686 | 0.6459 | 0.7110 | 0.6823 |
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| 0.1147 | 7.77 | 2000 | 0.1149 | 0.7838 | 0.7848 | 0.8368 | 0.8048 |
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| 0.1024 | 9.72 | 2500 | 0.1135 | 0.7802 | 0.7819 | 0.8340 | 0.8048 |
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| 0.0945 | 11.66 | 3000 | 0.1168 | 0.7891 | 0.7876 | 0.8418 | 0.8095 |
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| 0.0945 | 13.61 | 3500 | 0.1115 | 0.7918 | 0.7940 | 0.8472 | 0.8160 |
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### Framework versions
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config.json
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],
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"attention_dropout": 0.0094,
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"bos_token_id": 1,
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"classifier_proj_size":
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"codevector_dim": 768,
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"conformer_conv_dropout": 0.1,
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"contrastive_logits_temperature": 0.1,
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"left_max_position_embeddings": 64,
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"mask_feature_length": 5,
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"mask_feature_min_masks": 5,
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"mask_feature_prob": 0.
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"mask_time_length": 5,
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"mask_time_min_masks": 5,
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"mask_time_prob": 0.
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"max_source_positions": 5000,
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"model_type": "wav2vec2-bert",
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"num_adapter_layers": 1,
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"num_attention_heads": 16,
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"num_codevector_groups": 2,
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"num_codevectors_per_group": 320,
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"num_hidden_layers":
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"num_negatives": 100,
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"output_hidden_size": 1024,
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"pad_token_id": 0,
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],
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"attention_dropout": 0.0094,
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"bos_token_id": 1,
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"classifier_proj_size": 64,
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"codevector_dim": 768,
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"conformer_conv_dropout": 0.1,
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"contrastive_logits_temperature": 0.1,
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"left_max_position_embeddings": 64,
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"mask_feature_length": 5,
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"mask_feature_min_masks": 5,
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"mask_feature_prob": 0.00575,
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"mask_time_length": 5,
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"mask_time_min_masks": 5,
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"mask_time_prob": 0.00585,
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"max_source_positions": 5000,
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"model_type": "wav2vec2-bert",
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"num_adapter_layers": 1,
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"num_attention_heads": 16,
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"num_codevector_groups": 2,
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"num_codevectors_per_group": 320,
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"num_hidden_layers": 10,
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"num_negatives": 100,
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"output_hidden_size": 1024,
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"pad_token_id": 0,
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model.safetensors
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size 1000576520
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training_args.bin
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