End of training

README.md

@@ -1,199 +1,104 @@
 ---
-library_name: transformers
-tags: []
+license: cc-by-nc-4.0
+base_model: nguyenvulebinh/wav2vec2-base-vietnamese-250h
+tags:
+- generated_from_trainer
+datasets:
+- common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: model_weight_with_token_110
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: common_voice_11_0
+      type: common_voice_11_0
+      config: vi
+      split: None
+      args: vi
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.17328485312410297
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
-
-## Model Details
-
-### Model Description
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-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
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-## Uses
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-## How to Get Started with the Model
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-Use the code below to get started with the model.
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-## Training Details
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-### Training Data
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-#### Training Hyperparameters
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-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
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+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# model_weight_with_token_110
+
+This model is a fine-tuned version of [nguyenvulebinh/wav2vec2-base-vietnamese-250h](https://huggingface.co/nguyenvulebinh/wav2vec2-base-vietnamese-250h) on the common_voice_11_0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0688
+- Wer: 0.1733
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0001
+- train_batch_size: 32
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 40
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
+|:-------------:|:-------:|:-----:|:---------------:|:------:|
+| 0.5366        | 1.3928  | 500   | 0.1234          | 0.2107 |
+| 0.4976        | 2.7855  | 1000  | 0.1343          | 0.2133 |
+| 0.4734        | 4.1783  | 1500  | 0.1109          | 0.2037 |
+| 0.4449        | 5.5710  | 2000  | 0.1111          | 0.2061 |
+| 0.4194        | 6.9638  | 2500  | 0.1096          | 0.2024 |
+| 0.3941        | 8.3565  | 3000  | 0.1231          | 0.1969 |
+| 0.3767        | 9.7493  | 3500  | 0.1059          | 0.2002 |
+| 0.3853        | 11.1421 | 4000  | 0.0998          | 0.1930 |
+| 0.3584        | 12.5348 | 4500  | 0.0892          | 0.1905 |
+| 0.3291        | 13.9276 | 5000  | 0.0926          | 0.1899 |
+| 0.3279        | 15.3203 | 5500  | 0.0879          | 0.1878 |
+| 0.3014        | 16.7131 | 6000  | 0.0831          | 0.1851 |
+| 0.2886        | 18.1058 | 6500  | 0.0814          | 0.1857 |
+| 0.2949        | 19.4986 | 7000  | 0.0880          | 0.1854 |
+| 0.2661        | 20.8914 | 7500  | 0.0782          | 0.1829 |
+| 0.2676        | 22.2841 | 8000  | 0.0789          | 0.1806 |
+| 0.2663        | 23.6769 | 8500  | 0.0787          | 0.1805 |
+| 0.2461        | 25.0696 | 9000  | 0.0788          | 0.1793 |
+| 0.2484        | 26.4624 | 9500  | 0.0755          | 0.1804 |
+| 0.2452        | 27.8552 | 10000 | 0.0715          | 0.1773 |
+| 0.2261        | 29.2479 | 10500 | 0.0705          | 0.1764 |
+| 0.2311        | 30.6407 | 11000 | 0.0757          | 0.1770 |
+| 0.2195        | 32.0334 | 11500 | 0.0714          | 0.1763 |
+| 0.2208        | 33.4262 | 12000 | 0.0697          | 0.1752 |
+| 0.2029        | 34.8189 | 12500 | 0.0673          | 0.1744 |
+| 0.2228        | 36.2117 | 13000 | 0.0691          | 0.1739 |
+| 0.2056        | 37.6045 | 13500 | 0.0678          | 0.1738 |
+| 0.2017        | 38.9972 | 14000 | 0.0688          | 0.1733 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

config.json

@@ -0,0 +1,109 @@
+{
+  "_name_or_path": "nguyenvulebinh/wav2vec2-base-vietnamese-250h",
+  "activation_dropout": 0.1,
+  "adapter_attn_dim": null,
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": false,
+  "apply_spec_augment": true,
+  "architectures": [
+    "Wav2Vec2ForCTC"
+  ],
+  "attention_dropout": 0.1,
+  "bos_token_id": 1,
+  "classifier_proj_size": 256,
+  "codevector_dim": 256,
+  "contrastive_logits_temperature": 0.1,
+  "conv_bias": false,
+  "conv_dim": [
+    512,
+    512,
+    512,
+    512,
+    512,
+    512,
+    512
+  ],
+  "conv_kernel": [
+    10,
+    3,
+    3,
+    3,
+    3,
+    2,
+    2
+  ],
+  "conv_stride": [
+    5,
+    2,
+    2,
+    2,
+    2,
+    2,
+    2
+  ],
+  "ctc_loss_reduction": "mean",
+  "ctc_zero_infinity": false,
+  "diversity_loss_weight": 0.1,
+  "do_stable_layer_norm": false,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_dropout": 0.0,
+  "feat_extract_norm": "group",
+  "feat_proj_dropout": 0.1,
+  "feat_quantizer_dropout": 0.0,
+  "final_dropout": 0.1,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.1,
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.1,
+  "mask_feature_length": 10,
+  "mask_feature_min_masks": 0,
+  "mask_feature_prob": 0.0,
+  "mask_time_length": 10,
+  "mask_time_min_masks": 2,
+  "mask_time_prob": 0.05,
+  "model_type": "wav2vec2",
+  "num_adapter_layers": 3,
+  "num_attention_heads": 12,
+  "num_codevector_groups": 2,
+  "num_codevectors_per_group": 320,
+  "num_conv_pos_embedding_groups": 16,
+  "num_conv_pos_embeddings": 128,
+  "num_feat_extract_layers": 7,
+  "num_hidden_layers": 12,
+  "num_negatives": 100,
+  "output_hidden_size": 768,
+  "pad_token_id": 109,
+  "proj_codevector_dim": 256,
+  "tdnn_dilation": [
+    1,
+    2,
+    3,
+    1,
+    1
+  ],
+  "tdnn_dim": [
+    512,
+    512,
+    512,
+    512,
+    1500
+  ],
+  "tdnn_kernel": [
+    5,
+    3,
+    3,
+    1,
+    1
+  ],
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.2",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 110,
+  "xvector_output_dim": 512
+}

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preprocessor_config.json

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+{
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}

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