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yoon1000
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ft_0124_korean_2

Automatic Speech Recognition
Transformers
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Community
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  2. model.safetensors +1 -1
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: facebook/wav2vec2-xls-r-300m
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: ft_0124_korean_2
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+ results: []
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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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+ # ft_0124_korean_2
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5092
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+ - Cer: 0.1001
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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: 0.0001
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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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: 20
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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 | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 25.0263 | 0.25 | 500 | 5.1785 | 1.0 |
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+ | 4.7178 | 0.5 | 1000 | 4.7781 | 1.0 |
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+ | 4.4523 | 0.76 | 1500 | 4.1013 | 0.9077 |
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+ | 3.2148 | 1.01 | 2000 | 2.3856 | 0.4777 |
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+ | 2.4229 | 1.26 | 2500 | 1.8502 | 0.4047 |
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+ | 2.0145 | 1.51 | 3000 | 1.5497 | 0.3475 |
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+ | 1.7916 | 1.77 | 3500 | 1.3324 | 0.3076 |
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+ | 1.5849 | 2.02 | 4000 | 1.1873 | 0.2773 |
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+ | 1.3956 | 2.27 | 4500 | 1.0617 | 0.2578 |
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+ | 1.3086 | 2.52 | 5000 | 0.9643 | 0.2368 |
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+ | 1.2211 | 2.78 | 5500 | 0.8894 | 0.2246 |
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+ | 1.1562 | 3.03 | 6000 | 0.8537 | 0.2189 |
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+ | 1.0729 | 3.28 | 6500 | 0.7973 | 0.2101 |
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+ | 1.0089 | 3.53 | 7000 | 0.7549 | 0.1959 |
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+ | 1.0027 | 3.79 | 7500 | 0.7327 | 0.1945 |
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+ | 0.9496 | 4.04 | 8000 | 0.7082 | 0.1849 |
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+ | 0.887 | 4.29 | 8500 | 0.6909 | 0.1789 |
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+ | 0.8607 | 4.54 | 9000 | 0.6617 | 0.1739 |
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+ | 0.853 | 4.8 | 9500 | 0.6518 | 0.1730 |
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+ | 0.8305 | 5.05 | 10000 | 0.6402 | 0.1657 |
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+ | 0.774 | 5.3 | 10500 | 0.6365 | 0.1650 |
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+ | 0.7621 | 5.55 | 11000 | 0.6206 | 0.1600 |
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+ | 0.7553 | 5.81 | 11500 | 0.6080 | 0.1594 |
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+ | 0.7186 | 6.06 | 12000 | 0.5951 | 0.1543 |
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+ | 0.6772 | 6.31 | 12500 | 0.5814 | 0.1490 |
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+ | 0.6752 | 6.56 | 13000 | 0.5815 | 0.1501 |
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+ | 0.672 | 6.81 | 13500 | 0.5603 | 0.1440 |
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+ | 0.6351 | 7.07 | 14000 | 0.5670 | 0.1439 |
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+ | 0.6186 | 7.32 | 14500 | 0.5700 | 0.1431 |
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+ | 0.6035 | 7.57 | 15000 | 0.5614 | 0.1417 |
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+ | 0.5848 | 7.82 | 15500 | 0.5470 | 0.1396 |
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+ | 0.5719 | 8.08 | 16000 | 0.5514 | 0.1386 |
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+ | 0.556 | 8.33 | 16500 | 0.5515 | 0.1376 |
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+ | 0.5596 | 8.58 | 17000 | 0.5407 | 0.1325 |
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+ | 0.5472 | 8.83 | 17500 | 0.5405 | 0.1349 |
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+ | 0.5309 | 9.09 | 18000 | 0.5279 | 0.1295 |
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+ | 0.5072 | 9.34 | 18500 | 0.5275 | 0.1310 |
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+ | 0.5072 | 9.59 | 19000 | 0.5330 | 0.1272 |
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+ | 0.4905 | 9.84 | 19500 | 0.5238 | 0.1262 |
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+ | 0.4842 | 10.1 | 20000 | 0.5234 | 0.1237 |
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+ | 0.4513 | 10.35 | 20500 | 0.5210 | 0.1231 |
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+ | 0.4513 | 10.6 | 21000 | 0.5165 | 0.1208 |
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+ | 0.4541 | 10.85 | 21500 | 0.5189 | 0.1207 |
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+ | 0.4417 | 11.11 | 22000 | 0.5209 | 0.1192 |
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+ | 0.4337 | 11.36 | 22500 | 0.5246 | 0.1191 |
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+ | 0.4339 | 11.61 | 23000 | 0.5210 | 0.1183 |
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+ | 0.4357 | 11.86 | 23500 | 0.4990 | 0.1162 |
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+ | 0.4066 | 12.12 | 24000 | 0.4956 | 0.1132 |
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+ | 0.3932 | 12.37 | 24500 | 0.5064 | 0.1148 |
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+ | 0.384 | 12.62 | 25000 | 0.5011 | 0.1134 |
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+ | 0.3902 | 12.87 | 25500 | 0.5064 | 0.1130 |
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+ | 0.3883 | 13.12 | 26000 | 0.5128 | 0.1121 |
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+ | 0.3625 | 13.38 | 26500 | 0.5140 | 0.1119 |
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+ | 0.3648 | 13.63 | 27000 | 0.5091 | 0.1108 |
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+ | 0.365 | 13.88 | 27500 | 0.4923 | 0.1098 |
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+ | 0.3604 | 14.13 | 28000 | 0.5062 | 0.1090 |
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+ | 0.3517 | 14.39 | 28500 | 0.5007 | 0.1089 |
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+ | 0.3485 | 14.64 | 29000 | 0.4956 | 0.1081 |
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+ | 0.3407 | 14.89 | 29500 | 0.5090 | 0.1084 |
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+ | 0.333 | 15.14 | 30000 | 0.5018 | 0.1067 |
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+ | 0.3211 | 15.4 | 30500 | 0.5114 | 0.1063 |
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+ | 0.3204 | 15.65 | 31000 | 0.4976 | 0.1053 |
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+ | 0.3265 | 15.9 | 31500 | 0.4947 | 0.1046 |
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+ | 0.3169 | 16.15 | 32000 | 0.4988 | 0.1043 |
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+ | 0.304 | 16.41 | 32500 | 0.5115 | 0.1041 |
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+ | 0.2944 | 16.66 | 33000 | 0.5144 | 0.1042 |
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+ | 0.311 | 16.91 | 33500 | 0.5068 | 0.1025 |
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+ | 0.2997 | 17.16 | 34000 | 0.5079 | 0.1030 |
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+ | 0.288 | 17.42 | 34500 | 0.5065 | 0.1019 |
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+ | 0.2897 | 17.67 | 35000 | 0.5077 | 0.1016 |
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+ | 0.2939 | 17.92 | 35500 | 0.5003 | 0.1017 |
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+ | 0.2766 | 18.17 | 36000 | 0.5116 | 0.1013 |
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+ | 0.2841 | 18.43 | 36500 | 0.5019 | 0.1010 |
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+ | 0.2882 | 18.68 | 37000 | 0.5046 | 0.1008 |
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+ | 0.2678 | 18.93 | 37500 | 0.5086 | 0.1013 |
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+ | 0.269 | 19.18 | 38000 | 0.5108 | 0.1001 |
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+ | 0.2815 | 19.43 | 38500 | 0.5111 | 0.1001 |
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+ | 0.2668 | 19.69 | 39000 | 0.5091 | 0.1000 |
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+ | 0.2715 | 19.94 | 39500 | 0.5092 | 0.1001 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.36.2
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+ - Pytorch 2.1.2+cu118
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+ - Datasets 2.16.1
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+ - Tokenizers 0.15.0
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