shivamtiwari2112
commited on
Commit
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Parent(s):
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End of training
Browse files- README.md +85 -0
- config.json +82 -0
- model.safetensors +3 -0
- training_args.bin +3 -0
README.md
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---
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license: mit
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base_model: facebook/w2v-bert-2.0
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_16_0
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metrics:
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- wer
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model-index:
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- name: w2v-bert-2.0-hindi-colab-CV16.0
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: common_voice_16_0
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type: common_voice_16_0
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config: hi
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split: test
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args: hi
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metrics:
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- name: Wer
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type: wer
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value: 0.19428906708390378
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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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# w2v-bert-2.0-hindi-colab-CV16.0
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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 the common_voice_16_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3986
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- Wer: 0.1943
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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- seed: 42
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- gradient_accumulation_steps: 2
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- total_train_batch_size: 32
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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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- num_epochs: 10
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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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| 4.1542 | 1.35 | 300 | 0.8095 | 0.5287 |
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| 0.3259 | 2.71 | 600 | 0.4394 | 0.3296 |
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| 0.182 | 4.06 | 900 | 0.3599 | 0.2411 |
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| 0.0988 | 5.42 | 1200 | 0.3444 | 0.2149 |
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| 0.0617 | 6.77 | 1500 | 0.3469 | 0.2018 |
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| 0.0312 | 8.13 | 1800 | 0.3702 | 0.1937 |
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| 0.0137 | 9.48 | 2100 | 0.3986 | 0.1943 |
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### Framework versions
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- Transformers 4.37.0.dev0
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- Pytorch 2.1.2+cu121
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- Datasets 2.16.1
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- Tokenizers 0.15.0
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config.json
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{
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"_name_or_path": "facebook/w2v-bert-2.0",
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"activation_dropout": 0.0,
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"adapter_act": "relu",
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"adapter_kernel_size": 3,
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"adapter_stride": 2,
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"add_adapter": true,
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"apply_spec_augment": false,
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"architectures": [
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"Wav2Vec2BertForCTC"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"classifier_proj_size": 768,
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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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"conv_depthwise_kernel_size": 31,
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"ctc_loss_reduction": "mean",
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"ctc_zero_infinity": false,
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"diversity_loss_weight": 0.1,
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"eos_token_id": 2,
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"feat_proj_dropout": 0.0,
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"feat_quantizer_dropout": 0.0,
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"feature_projection_input_dim": 160,
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"final_dropout": 0.1,
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"hidden_act": "swish",
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"hidden_dropout": 0.0,
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"hidden_size": 1024,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.0,
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"left_max_position_embeddings": 64,
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"mask_feature_length": 10,
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"mask_feature_min_masks": 0,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_min_masks": 2,
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"mask_time_prob": 0.0,
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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": 24,
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"num_negatives": 100,
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"output_hidden_size": 1024,
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"pad_token_id": 74,
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"position_embeddings_type": "relative_key",
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"proj_codevector_dim": 768,
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"right_max_position_embeddings": 8,
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"rotary_embedding_base": 10000,
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"tdnn_dilation": [
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1,
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1,
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],
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"tdnn_dim": [
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512,
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512,
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512,
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512,
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1500
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],
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"tdnn_kernel": [
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5,
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1,
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1
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],
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"torch_dtype": "float32",
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"transformers_version": "4.37.0.dev0",
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"use_intermediate_ffn_before_adapter": false,
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"use_weighted_layer_sum": false,
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"vocab_size": 77,
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"xvector_output_dim": 512
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5ee017a8b2ae60b19db59475d6f7fd09baa8746774c18d59f4d7147b596bcabf
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size 2423130260
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:7a7c0b687a924b7dffa573c4278d42b6a35f29524baaa4034527f46a41242aa3
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size 4664
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