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End of training

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  1. README.md +85 -0
  2. config.json +82 -0
  3. model.safetensors +3 -0
  4. training_args.bin +3 -0
README.md ADDED
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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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+
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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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+
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+ # w2v-bert-2.0-hindi-colab-CV16.0
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+
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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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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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
config.json ADDED
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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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+ ],
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+ "tdnn_dim": [
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+ 512,
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+ 1500
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+ ],
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+ "tdnn_kernel": [
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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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