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@ -23,10 +23,10 @@ model-index:
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metrics:
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metrics:
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- name: Test WER
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- name: Test WER
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type: wer
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type: wer
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value: 29.30
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value: 27.08
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---
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---
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# Wav2Vec2-Base-960-Turkish
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# Wav2Vec2-Base-760-Turkish
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# TBA
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# TBA
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Pretrained Turkish model [ceyda/wav2vec2-base-760](https://huggingface.co/ceyda/wav2vec2-base-760). Fine-tuned on Turkish using the [Common Voice](https://huggingface.co/datasets/common_voice)
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Pretrained Turkish model [ceyda/wav2vec2-base-760](https://huggingface.co/ceyda/wav2vec2-base-760). Fine-tuned on Turkish using the [Common Voice](https://huggingface.co/datasets/common_voice)
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@ -87,7 +87,7 @@ processor = Wav2Vec2Processor.from_pretrained("ceyda/wav2vec2-base-960-turkish")
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model = Wav2Vec2ForCTC.from_pretrained("ceyda/wav2vec2-base-960-turkish")
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model = Wav2Vec2ForCTC.from_pretrained("ceyda/wav2vec2-base-960-turkish")
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model.to("cuda")
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model.to("cuda")
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chars_to_ignore_regex = '[\\,\\?\\.\\!\\-\\;\\:\\"\\“\\‘\\”\\'\\`…\\’»«]'
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chars_to_ignore_regex = '[\,\?\.\!\-\;\:\"\“\‘\”\'\`…\’»«]'
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resampler = torchaudio.transforms.Resample(48_000, 16_000)
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resampler = torchaudio.transforms.Resample(48_000, 16_000)
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# Preprocessing the datasets.
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# Preprocessing the datasets.
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@ -117,7 +117,7 @@ result = test_dataset.map(evaluate, batched=True, batch_size=8)
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print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"], references=result["sentence"])))
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print("WER: {:2f}".format(100 * wer.compute(predictions=result["pred_strings"], references=result["sentence"])))
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```
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```
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**Test Result**: XX.XX % (TBA)
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**Test Result**: 27.08 % (in progress)
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## Training
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## Training
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{
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"_name_or_path": "./pretrained/checkpoint_0.60",
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"activation_dropout": 0.1,
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"apply_spec_augment": true,
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"architectures": [
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"Wav2Vec2ForCTC"
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],
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"attention_dropout": 0.1,
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"bos_token_id": 1,
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"conv_bias": false,
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"conv_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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512,
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512,
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512
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],
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"conv_kernel": [
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10,
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3,
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3,
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3,
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3,
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2,
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2
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],
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"conv_stride": [
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5,
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2,
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2,
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2,
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2,
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2,
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2
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],
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"ctc_loss_reduction": "mean",
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"ctc_zero_infinity": true,
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"do_stable_layer_norm": false,
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"eos_token_id": 2,
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"feat_extract_activation": "gelu",
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"feat_extract_norm": "group",
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"feat_proj_dropout": 0.1,
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"final_dropout": 0.1,
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"gradient_checkpointing": true,
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"hidden_act": "gelu",
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"hidden_dropout": 0.05,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"layerdrop": 0.1,
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"mask_feature_length": 10,
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"mask_feature_prob": 0.0,
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"mask_time_length": 10,
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"mask_time_prob": 0.5,
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"model_type": "wav2vec2",
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"num_attention_heads": 12,
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"num_conv_pos_embedding_groups": 16,
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"num_conv_pos_embeddings": 128,
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"num_feat_extract_layers": 7,
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"num_hidden_layers": 12,
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"pad_token_id": 36,
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"transformers_version": "4.5.0.dev0",
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"vocab_size": 37
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}
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{
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"do_normalize": true,
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"feature_size": 1,
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"padding_side": "right",
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"padding_value": 0.0,
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"return_attention_mask": true,
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"sampling_rate": 16000
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}
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@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:ecb5a521af5105ca67abd19a841c08e97b071a8b69e186b06b25633c6fc36804
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size 377690860
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@ -0,0 +1 @@
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{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "[UNK]", "pad_token": "[PAD]"}
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{"unk_token": "[UNK]", "bos_token": "<s>", "eos_token": "</s>", "pad_token": "[PAD]", "do_lower_case": false, "word_delimiter_token": "|"}
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@ -0,0 +1 @@
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{"e": 0, "x": 1, "î": 2, "l": 3, "â": 4, "j": 5, "ç": 6, "ş": 7, "g": 8, "ı": 9, "v": 10, "d": 11, "t": 12, "n": 13, "a": 14, "c": 15, "h": 16, "p": 17, "r": 18, "w": 19, "z": 20, "k": 21, "u": 22, "b": 23, "ü": 24, "y": 26, "o": 27, "q": 28, "m": 29, "f": 30, "s": 31, "ö": 32, "ğ": 33, "i": 34, "|": 25, "[UNK]": 35, "[PAD]": 36}
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