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.gitignore

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+checkpoint-*/

LICENSE.md

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README.md

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+---
+language: en
+license: apache-2.0
+tags:
+- audio-classification
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+base_model: wav2vec2-base
+model-index:
+- name: wav2vec2-adult-child-cls
+  results: []
+---
+
+# Wav2Vec2 Adult/Child Speech Classifier
+
+Wav2Vec2 Adult/Child Speech Classifier is an audio classification model based on the [wav2vec 2.0](https://arxiv.org/abs/2006.11477) architecture. This model is a fine-tuned version of [wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on a private adult/child speech classification dataset.
+
+This model was trained using HuggingFace's PyTorch framework. All training was done on a Tesla P100, provided by Kaggle. Training metrics were logged via Tensorboard.
+
+## Model
+
+| Model                      | #params | Arch.       | Training/Validation data (text)           |
+| -------------------------- | ------- | ----------- | ----------------------------------------- |
+| `wav2vec2-adult-child-cls` | 91M     | wav2vec 2.0 | Adult/Child Speech Classification Dataset |
+
+## Evaluation Results
+
+The model achieves the following results on evaluation:
+
+| Dataset                           | Loss   | Accuracy | F1     |
+| --------------------------------- | ------ | -------- | ------ |
+| Adult/Child Speech Classification | 0.1682 | 95.80%   | 0.9618 |
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+
+- `learning_rate`: 3e-05
+- `train_batch_size`: 32
+- `eval_batch_size`: 32
+- `seed`: 42
+- `optimizer`: Adam with `betas=(0.9,0.999)` and `epsilon=1e-08`
+- `lr_scheduler_type`: linear
+- `lr_scheduler_warmup_ratio`: 0.1
+- `num_epochs`: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |   F1   |
+| :-----------: | :---: | :--: | :-------------: | :------: | :----: |
+|    0.2709     |  1.0  | 384  |     0.2616      |  0.9104  | 0.9142 |
+|    0.2112     |  2.0  | 768  |     0.1826      |  0.9386  | 0.9421 |
+|    0.1755     |  3.0  | 1152 |     0.1898      |  0.9354  | 0.9428 |
+|    0.0915     |  4.0  | 1536 |     0.1682      |  0.9580  | 0.9618 |
+|    0.1042     |  5.0  | 1920 |     0.1717      |  0.9511  | 0.9554 |
+
+## Disclaimer
+
+Do consider the biases which came from pre-training datasets that may be carried over into the results of this model.
+
+## Authors
+
+Wav2Vec2 Adult/Child Speech Classifier was trained and evaluated by [Wilson Wongso](https://w11wo.github.io/). All computation and development are done on Kaggle.
+
+## Framework versions
+
+- Transformers 4.16.2
+- Pytorch 1.10.2+cu102
+- Datasets 1.18.3
+- Tokenizers 0.10.3

config.json

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+{
+  "_name_or_path": "facebook/wav2vec2-base",
+  "activation_dropout": 0.0,
+  "adapter_kernel_size": 3,
+  "adapter_stride": 2,
+  "add_adapter": false,
+  "apply_spec_augment": true,
+  "architectures": [
+    "Wav2Vec2ForSequenceClassification"
+  ],
+  "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": "sum",
+  "ctc_zero_infinity": false,
+  "diversity_loss_weight": 0.1,
+  "do_stable_layer_norm": false,
+  "eos_token_id": 2,
+  "feat_extract_activation": "gelu",
+  "feat_extract_norm": "group",
+  "feat_proj_dropout": 0.1,
+  "feat_quantizer_dropout": 0.0,
+  "final_dropout": 0.0,
+  "freeze_feat_extract_train": true,
+  "hidden_act": "gelu",
+  "hidden_dropout": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "adult",
+    "1": "child"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "adult": 0,
+    "child": 1
+  },
+  "layer_norm_eps": 1e-05,
+  "layerdrop": 0.0,
+  "mask_channel_length": 10,
+  "mask_channel_min_space": 1,
+  "mask_channel_other": 0.0,
+  "mask_channel_prob": 0.0,
+  "mask_channel_selection": "static",
+  "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_min_space": 1,
+  "mask_time_other": 0.0,
+  "mask_time_prob": 0.05,
+  "mask_time_selection": "static",
+  "model_type": "wav2vec2",
+  "no_mask_channel_overlap": false,
+  "no_mask_time_overlap": false,
+  "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": 0,
+  "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": "4.16.2",
+  "use_weighted_layer_sum": false,
+  "vocab_size": 32,
+  "xvector_output_dim": 512
+}

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+  "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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