End of training

README.md

@@ -1,199 +1,106 @@
 ---
-library_name: transformers
-tags: []
+license: apache-2.0
+base_model: facebook/wav2vec2-xls-r-300m
+tags:
+- generated_from_trainer
+metrics:
+- wer
+model-index:
+- name: wav2vec2-base-vivos
+  results: []
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-
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-## Model Details
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-### Model Description
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-<!-- Provide a longer summary of what this model is. -->
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-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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+<!-- 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. -->
+
+# wav2vec2-base-vivos
+
+This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5366
+- Wer: 0.3320
+
+## 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: 8
+- 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: 30
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Wer    |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|
+| 7.987         | 0.66  | 500   | 3.5460          | 1.0    |
+| 3.4026        | 1.31  | 1000  | 3.0685          | 1.0    |
+| 1.6402        | 1.97  | 1500  | 0.7959          | 0.7082 |
+| 0.8229        | 2.62  | 2000  | 0.5581          | 0.5326 |
+| 0.6392        | 3.28  | 2500  | 0.4779          | 0.4738 |
+| 0.5532        | 3.94  | 3000  | 0.4415          | 0.4491 |
+| 0.4937        | 4.59  | 3500  | 0.4318          | 0.4312 |
+| 0.4506        | 5.25  | 4000  | 0.4284          | 0.4134 |
+| 0.4099        | 5.91  | 4500  | 0.4405          | 0.4267 |
+| 0.3848        | 6.56  | 5000  | 0.4097          | 0.3987 |
+| 0.3683        | 7.22  | 5500  | 0.4239          | 0.4031 |
+| 0.3485        | 7.87  | 6000  | 0.4383          | 0.3926 |
+| 0.3313        | 8.53  | 6500  | 0.4779          | 0.3846 |
+| 0.321         | 9.19  | 7000  | 0.4623          | 0.3895 |
+| 0.3058        | 9.84  | 7500  | 0.4668          | 0.3906 |
+| 0.2869        | 10.5  | 8000  | 0.4817          | 0.3749 |
+| 0.2828        | 11.15 | 8500  | 0.4777          | 0.3789 |
+| 0.2724        | 11.81 | 9000  | 0.4915          | 0.3649 |
+| 0.2527        | 12.47 | 9500  | 0.4671          | 0.3670 |
+| 0.2588        | 13.12 | 10000 | 0.4693          | 0.3612 |
+| 0.2405        | 13.78 | 10500 | 0.4375          | 0.3579 |
+| 0.2409        | 14.44 | 11000 | 0.4643          | 0.3595 |
+| 0.2247        | 15.09 | 11500 | 0.5445          | 0.3626 |
+| 0.2257        | 15.75 | 12000 | 0.4474          | 0.3513 |
+| 0.2101        | 16.4  | 12500 | 0.4327          | 0.3502 |
+| 0.2118        | 17.06 | 13000 | 0.4830          | 0.3534 |
+| 0.1991        | 17.72 | 13500 | 0.4832          | 0.3454 |
+| 0.193         | 18.37 | 14000 | 0.4878          | 0.3547 |
+| 0.1909        | 19.03 | 14500 | 0.4777          | 0.3506 |
+| 0.1869        | 19.69 | 15000 | 0.4722          | 0.3455 |
+| 0.1801        | 20.34 | 15500 | 0.4891          | 0.3477 |
+| 0.1749        | 21.0  | 16000 | 0.5065          | 0.3446 |
+| 0.1715        | 21.65 | 16500 | 0.5381          | 0.3447 |
+| 0.1669        | 22.31 | 17000 | 0.4946          | 0.3459 |
+| 0.1674        | 22.97 | 17500 | 0.4968          | 0.3425 |
+| 0.1579        | 23.62 | 18000 | 0.5210          | 0.3370 |
+| 0.1566        | 24.28 | 18500 | 0.5318          | 0.3385 |
+| 0.1565        | 24.93 | 19000 | 0.4959          | 0.3381 |
+| 0.1517        | 25.59 | 19500 | 0.5181          | 0.3393 |
+| 0.1452        | 26.25 | 20000 | 0.5222          | 0.3359 |
+| 0.1419        | 26.9  | 20500 | 0.5316          | 0.3333 |
+| 0.1389        | 27.56 | 21000 | 0.5094          | 0.3302 |
+| 0.1422        | 28.22 | 21500 | 0.5327          | 0.3346 |
+| 0.1365        | 28.87 | 22000 | 0.5436          | 0.3320 |
+| 0.1337        | 29.53 | 22500 | 0.5366          | 0.3320 |
+
+
+### Framework versions
+
+- Transformers 4.39.3
+- Pytorch 2.1.2
+- Datasets 2.18.0
+- Tokenizers 0.15.2

config.json

@@ -0,0 +1,108 @@
+{
+  "_name_or_path": "facebook/wav2vec2-xls-r-300m",
+  "activation_dropout": 0.0,
+  "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": 768,
+  "contrastive_logits_temperature": 0.1,
+  "conv_bias": true,
+  "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": true,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_dropout": 0.0,
+  "feat_extract_norm": "layer",
+  "feat_proj_dropout": 0.0,
+  "feat_quantizer_dropout": 0.0,
+  "final_dropout": 0.0,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.1,
+  "hidden_size": 1024,
+  "initializer_range": 0.02,
+  "intermediate_size": 4096,
+  "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": 16,
+  "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": 24,
+  "num_negatives": 100,
+  "output_hidden_size": 1024,
+  "pad_token_id": 91,
+  "proj_codevector_dim": 768,
+  "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": "4.39.3",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 94,
+  "xvector_output_dim": 512
+}

model.safetensors

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+size 1262192880

preprocessor_config.json

@@ -0,0 +1,9 @@
+{
+  "do_normalize": true,
+  "feature_extractor_type": "Wav2Vec2FeatureExtractor",
+  "feature_size": 1,
+  "padding_side": "right",
+  "padding_value": 0.0,
+  "return_attention_mask": false,
+  "sampling_rate": 16000
+}

runs/Apr30_09-13-12_9045ca3668be/events.out.tfevents.1714468570.9045ca3668be.24.0

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training_args.bin

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