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anderloh
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HuggingfaceTest

Audio Classification
Transformers
PyTorch
TensorBoard
Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
Model card Files Metrics Community
anderloh commited on
Commit
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1 Parent(s): c864196

Training in progress, epoch 0

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Files changed (10) hide show
  1. README.md +293 -0
  2. config.json +124 -0
  3. model.safetensors +3 -0
  4. preprocessor_config.json +9 -0
  5. pytorch_model.bin +3 -0
  6. runs/Jun19_18-32-08_ml6.hpc.uio.no/events.out.tfevents.1718814757.ml6.hpc.uio.no.3740755.0 +3 -0
  7. runs/Jun19_19-59-24_ml6.hpc.uio.no/events.out.tfevents.1718819982.ml6.hpc.uio.no.3789351.0 +3 -0
  8. runs/May04_11-28-58_ml6.hpc.uio.no/events.out.tfevents.1714815008.ml6.hpc.uio.no.725046.0 +3 -0
  9. runs/May04_11-33-59_ml6.hpc.uio.no/events.out.tfevents.1714815251.ml6.hpc.uio.no.727136.0 +3 -0
  10. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ base_model: anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: PushToHubModel
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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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+ # PushToHubModel
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+
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+ This model is a fine-tuned version of [anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test](https://huggingface.co/anderloh/Hugginhface-master-wav2vec-pretreined-5-class-train-test) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.8947
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+ - Accuracy: 0.6748
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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: 3e-05
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+ - train_batch_size: 128
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+ - eval_batch_size: 128
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+ - seed: 0
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 512
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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_ratio: 0.1
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+ - num_epochs: 250.0
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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 | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | No log | 0.92 | 3 | 1.5989 | 0.3427 |
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+ | No log | 1.85 | 6 | 1.5987 | 0.3427 |
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+ | No log | 2.77 | 9 | 1.5984 | 0.3427 |
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+ | No log | 4.0 | 13 | 1.5977 | 0.3427 |
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+ | No log | 4.92 | 16 | 1.5970 | 0.3427 |
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+ | No log | 5.85 | 19 | 1.5963 | 0.3392 |
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+ | No log | 6.77 | 22 | 1.5953 | 0.3357 |
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+ | No log | 8.0 | 26 | 1.5938 | 0.3287 |
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+ | No log | 8.92 | 29 | 1.5925 | 0.3217 |
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+ | No log | 9.85 | 32 | 1.5911 | 0.3147 |
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+ | No log | 10.77 | 35 | 1.5896 | 0.3112 |
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+ | No log | 12.0 | 39 | 1.5873 | 0.3042 |
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+ | No log | 12.92 | 42 | 1.5854 | 0.3007 |
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+ | No log | 13.85 | 45 | 1.5834 | 0.2972 |
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+ | No log | 14.77 | 48 | 1.5813 | 0.2832 |
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+ | 1.5878 | 16.0 | 52 | 1.5784 | 0.2727 |
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+ | 1.5878 | 16.92 | 55 | 1.5760 | 0.2727 |
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+ | 1.5878 | 17.85 | 58 | 1.5736 | 0.2692 |
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+ | 1.5878 | 18.77 | 61 | 1.5711 | 0.2517 |
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+ | 1.5878 | 20.0 | 65 | 1.5675 | 0.2378 |
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+ | 1.5878 | 20.92 | 68 | 1.5645 | 0.2343 |
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+ | 1.5878 | 21.85 | 71 | 1.5613 | 0.2238 |
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+ | 1.5878 | 22.77 | 74 | 1.5581 | 0.2273 |
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+ | 1.5878 | 24.0 | 78 | 1.5537 | 0.2273 |
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+ | 1.5878 | 24.92 | 81 | 1.5504 | 0.2273 |
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+ | 1.5878 | 25.85 | 84 | 1.5473 | 0.2273 |
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+ | 1.5878 | 26.77 | 87 | 1.5444 | 0.2273 |
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+ | 1.5878 | 28.0 | 91 | 1.5405 | 0.2273 |
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+ | 1.5878 | 28.92 | 94 | 1.5378 | 0.2273 |
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+ | 1.5878 | 29.85 | 97 | 1.5353 | 0.2273 |
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+ | 1.5185 | 30.77 | 100 | 1.5335 | 0.2273 |
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+ | 1.5185 | 32.0 | 104 | 1.5322 | 0.2273 |
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+ | 1.5185 | 32.92 | 107 | 1.5323 | 0.2273 |
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+ | 1.5185 | 33.85 | 110 | 1.5341 | 0.2273 |
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+ | 1.5185 | 34.77 | 113 | 1.5373 | 0.2273 |
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+ | 1.5185 | 36.0 | 117 | 1.5437 | 0.2273 |
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+ | 1.5185 | 36.92 | 120 | 1.5511 | 0.2273 |
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+ | 1.5185 | 37.85 | 123 | 1.5605 | 0.2273 |
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+ | 1.5185 | 38.77 | 126 | 1.5712 | 0.2273 |
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+ | 1.5185 | 40.0 | 130 | 1.5858 | 0.2273 |
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+ | 1.5185 | 40.92 | 133 | 1.5946 | 0.2273 |
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+ | 1.5185 | 41.85 | 136 | 1.6022 | 0.2273 |
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+ | 1.5185 | 42.77 | 139 | 1.6077 | 0.2273 |
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+ | 1.5185 | 44.0 | 143 | 1.6055 | 0.2308 |
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+ | 1.5185 | 44.92 | 146 | 1.5978 | 0.2238 |
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+ | 1.5185 | 45.85 | 149 | 1.5862 | 0.2413 |
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+ | 1.3621 | 46.77 | 152 | 1.5746 | 0.2692 |
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+ | 1.3621 | 48.0 | 156 | 1.5576 | 0.2657 |
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+ | 1.3621 | 48.92 | 159 | 1.5446 | 0.2867 |
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+ | 1.3621 | 49.85 | 162 | 1.5347 | 0.3007 |
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+ | 1.3621 | 50.77 | 165 | 1.5267 | 0.3182 |
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+ | 1.3621 | 52.0 | 169 | 1.5192 | 0.3322 |
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+ | 1.3621 | 52.92 | 172 | 1.5158 | 0.3357 |
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+ | 1.3621 | 53.85 | 175 | 1.5128 | 0.3392 |
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+ | 1.3621 | 54.77 | 178 | 1.5093 | 0.3427 |
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+ | 1.3621 | 56.0 | 182 | 1.5042 | 0.3462 |
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+ | 1.3621 | 56.92 | 185 | 1.4979 | 0.3531 |
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+ | 1.3621 | 57.85 | 188 | 1.4927 | 0.3566 |
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+ | 1.3621 | 58.77 | 191 | 1.4858 | 0.3601 |
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+ | 1.3621 | 60.0 | 195 | 1.4790 | 0.3706 |
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+ | 1.3621 | 60.92 | 198 | 1.4717 | 0.3741 |
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+ | 1.2297 | 61.85 | 201 | 1.4674 | 0.3846 |
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+ | 1.2297 | 62.77 | 204 | 1.4588 | 0.3881 |
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+ | 1.2297 | 64.0 | 208 | 1.4482 | 0.4021 |
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+ | 1.2297 | 64.92 | 211 | 1.4374 | 0.4161 |
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+ | 1.2297 | 65.85 | 214 | 1.4255 | 0.4231 |
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+ | 1.2297 | 66.77 | 217 | 1.4126 | 0.4336 |
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+ | 1.2297 | 68.0 | 221 | 1.4000 | 0.4371 |
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+ | 1.2297 | 68.92 | 224 | 1.3919 | 0.4371 |
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+ | 1.2297 | 69.85 | 227 | 1.3865 | 0.4406 |
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+ | 1.2297 | 70.77 | 230 | 1.3836 | 0.4441 |
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+ | 1.2297 | 72.0 | 234 | 1.3742 | 0.4441 |
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+ | 1.2297 | 72.92 | 237 | 1.3636 | 0.4476 |
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+ | 1.2297 | 73.85 | 240 | 1.3518 | 0.4580 |
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+ | 1.2297 | 74.77 | 243 | 1.3429 | 0.4685 |
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+ | 1.2297 | 76.0 | 247 | 1.3334 | 0.4825 |
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+ | 1.1141 | 76.92 | 250 | 1.3253 | 0.4860 |
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+ | 1.1141 | 77.85 | 253 | 1.3172 | 0.4860 |
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+ | 1.1141 | 78.77 | 256 | 1.3118 | 0.4825 |
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+ | 1.1141 | 80.0 | 260 | 1.3054 | 0.4790 |
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+ | 1.1141 | 80.92 | 263 | 1.2986 | 0.4790 |
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+ | 1.1141 | 81.85 | 266 | 1.2907 | 0.4790 |
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+ | 1.1141 | 82.77 | 269 | 1.2791 | 0.4860 |
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+ | 1.1141 | 84.0 | 273 | 1.2688 | 0.4860 |
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+ | 1.1141 | 84.92 | 276 | 1.2623 | 0.4895 |
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+ | 1.1141 | 85.85 | 279 | 1.2557 | 0.4930 |
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+ | 1.1141 | 86.77 | 282 | 1.2547 | 0.5 |
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+ | 1.1141 | 88.0 | 286 | 1.2539 | 0.5070 |
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+ | 1.1141 | 88.92 | 289 | 1.2504 | 0.5070 |
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+ | 1.1141 | 89.85 | 292 | 1.2435 | 0.5070 |
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+ | 1.1141 | 90.77 | 295 | 1.2374 | 0.5070 |
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+ | 1.1141 | 92.0 | 299 | 1.2278 | 0.5140 |
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+ | 1.0055 | 92.92 | 302 | 1.2204 | 0.5210 |
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+ | 1.0055 | 93.85 | 305 | 1.2155 | 0.5210 |
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+ | 1.0055 | 94.77 | 308 | 1.2131 | 0.5210 |
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+ | 1.0055 | 96.0 | 312 | 1.2082 | 0.5280 |
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+ | 1.0055 | 96.92 | 315 | 1.2022 | 0.5350 |
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+ | 1.0055 | 97.85 | 318 | 1.1926 | 0.5350 |
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+ | 1.0055 | 98.77 | 321 | 1.1854 | 0.5420 |
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+ | 1.0055 | 100.0 | 325 | 1.1779 | 0.5455 |
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+ | 1.0055 | 100.92 | 328 | 1.1747 | 0.5490 |
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+ | 1.0055 | 101.85 | 331 | 1.1715 | 0.5490 |
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+ | 1.0055 | 102.77 | 334 | 1.1681 | 0.5490 |
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+ | 1.0055 | 104.0 | 338 | 1.1552 | 0.5524 |
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+ | 1.0055 | 104.92 | 341 | 1.1457 | 0.5594 |
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+ | 1.0055 | 105.85 | 344 | 1.1385 | 0.5629 |
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+ | 1.0055 | 106.77 | 347 | 1.1312 | 0.5699 |
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+ | 0.9214 | 108.0 | 351 | 1.1231 | 0.5769 |
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+ | 0.9214 | 108.92 | 354 | 1.1204 | 0.5804 |
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+ | 0.9214 | 109.85 | 357 | 1.1177 | 0.5769 |
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+ | 0.9214 | 110.77 | 360 | 1.1143 | 0.5804 |
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+ | 0.9214 | 112.0 | 364 | 1.1112 | 0.5769 |
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+ | 0.9214 | 112.92 | 367 | 1.1073 | 0.5944 |
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+ | 0.9214 | 113.85 | 370 | 1.1025 | 0.5944 |
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+ | 0.9214 | 114.77 | 373 | 1.0935 | 0.6049 |
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+ | 0.9214 | 116.0 | 377 | 1.0794 | 0.6049 |
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+ | 0.9214 | 116.92 | 380 | 1.0689 | 0.6084 |
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+ | 0.9214 | 117.85 | 383 | 1.0585 | 0.6189 |
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+ | 0.9214 | 118.77 | 386 | 1.0515 | 0.6259 |
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+ | 0.9214 | 120.0 | 390 | 1.0456 | 0.6189 |
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+ | 0.9214 | 120.92 | 393 | 1.0421 | 0.6189 |
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+ | 0.9214 | 121.85 | 396 | 1.0393 | 0.6189 |
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+ | 0.9214 | 122.77 | 399 | 1.0351 | 0.6189 |
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+ | 0.8358 | 124.0 | 403 | 1.0309 | 0.6189 |
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+ | 0.8358 | 124.92 | 406 | 1.0282 | 0.6189 |
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+ | 0.8358 | 125.85 | 409 | 1.0239 | 0.6189 |
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+ | 0.8358 | 126.77 | 412 | 1.0165 | 0.6259 |
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+ | 0.8358 | 128.0 | 416 | 1.0052 | 0.6294 |
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+ | 0.8358 | 128.92 | 419 | 0.9978 | 0.6329 |
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+ | 0.8358 | 129.85 | 422 | 0.9944 | 0.6399 |
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+ | 0.8358 | 130.77 | 425 | 0.9936 | 0.6399 |
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+ | 0.8358 | 132.0 | 429 | 0.9909 | 0.6399 |
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+ | 0.8358 | 132.92 | 432 | 0.9893 | 0.6434 |
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+ | 0.8358 | 133.85 | 435 | 0.9849 | 0.6469 |
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+ | 0.8358 | 134.77 | 438 | 0.9814 | 0.6469 |
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+ | 0.8358 | 136.0 | 442 | 0.9776 | 0.6434 |
191
+ | 0.8358 | 136.92 | 445 | 0.9732 | 0.6503 |
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+ | 0.8358 | 137.85 | 448 | 0.9680 | 0.6503 |
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+ | 0.773 | 138.77 | 451 | 0.9665 | 0.6503 |
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+ | 0.773 | 140.0 | 455 | 0.9641 | 0.6503 |
195
+ | 0.773 | 140.92 | 458 | 0.9629 | 0.6538 |
196
+ | 0.773 | 141.85 | 461 | 0.9600 | 0.6538 |
197
+ | 0.773 | 142.77 | 464 | 0.9584 | 0.6503 |
198
+ | 0.773 | 144.0 | 468 | 0.9512 | 0.6538 |
199
+ | 0.773 | 144.92 | 471 | 0.9475 | 0.6538 |
200
+ | 0.773 | 145.85 | 474 | 0.9492 | 0.6538 |
201
+ | 0.773 | 146.77 | 477 | 0.9511 | 0.6573 |
202
+ | 0.773 | 148.0 | 481 | 0.9548 | 0.6608 |
203
+ | 0.773 | 148.92 | 484 | 0.9539 | 0.6573 |
204
+ | 0.773 | 149.85 | 487 | 0.9493 | 0.6678 |
205
+ | 0.773 | 150.77 | 490 | 0.9428 | 0.6678 |
206
+ | 0.773 | 152.0 | 494 | 0.9381 | 0.6643 |
207
+ | 0.773 | 152.92 | 497 | 0.9356 | 0.6643 |
208
+ | 0.7252 | 153.85 | 500 | 0.9317 | 0.6643 |
209
+ | 0.7252 | 154.77 | 503 | 0.9293 | 0.6643 |
210
+ | 0.7252 | 156.0 | 507 | 0.9327 | 0.6678 |
211
+ | 0.7252 | 156.92 | 510 | 0.9338 | 0.6678 |
212
+ | 0.7252 | 157.85 | 513 | 0.9341 | 0.6643 |
213
+ | 0.7252 | 158.77 | 516 | 0.9338 | 0.6643 |
214
+ | 0.7252 | 160.0 | 520 | 0.9282 | 0.6643 |
215
+ | 0.7252 | 160.92 | 523 | 0.9234 | 0.6678 |
216
+ | 0.7252 | 161.85 | 526 | 0.9192 | 0.6678 |
217
+ | 0.7252 | 162.77 | 529 | 0.9182 | 0.6678 |
218
+ | 0.7252 | 164.0 | 533 | 0.9217 | 0.6678 |
219
+ | 0.7252 | 164.92 | 536 | 0.9230 | 0.6643 |
220
+ | 0.7252 | 165.85 | 539 | 0.9247 | 0.6678 |
221
+ | 0.7252 | 166.77 | 542 | 0.9255 | 0.6713 |
222
+ | 0.7252 | 168.0 | 546 | 0.9225 | 0.6713 |
223
+ | 0.7252 | 168.92 | 549 | 0.9201 | 0.6713 |
224
+ | 0.697 | 169.85 | 552 | 0.9186 | 0.6678 |
225
+ | 0.697 | 170.77 | 555 | 0.9153 | 0.6678 |
226
+ | 0.697 | 172.0 | 559 | 0.9132 | 0.6713 |
227
+ | 0.697 | 172.92 | 562 | 0.9127 | 0.6713 |
228
+ | 0.697 | 173.85 | 565 | 0.9122 | 0.6713 |
229
+ | 0.697 | 174.77 | 568 | 0.9141 | 0.6713 |
230
+ | 0.697 | 176.0 | 572 | 0.9148 | 0.6713 |
231
+ | 0.697 | 176.92 | 575 | 0.9140 | 0.6713 |
232
+ | 0.697 | 177.85 | 578 | 0.9140 | 0.6713 |
233
+ | 0.697 | 178.77 | 581 | 0.9127 | 0.6713 |
234
+ | 0.697 | 180.0 | 585 | 0.9130 | 0.6748 |
235
+ | 0.697 | 180.92 | 588 | 0.9104 | 0.6748 |
236
+ | 0.697 | 181.85 | 591 | 0.9088 | 0.6748 |
237
+ | 0.697 | 182.77 | 594 | 0.9052 | 0.6748 |
238
+ | 0.697 | 184.0 | 598 | 0.9011 | 0.6748 |
239
+ | 0.6822 | 184.92 | 601 | 0.8989 | 0.6748 |
240
+ | 0.6822 | 185.85 | 604 | 0.8974 | 0.6748 |
241
+ | 0.6822 | 186.77 | 607 | 0.8963 | 0.6748 |
242
+ | 0.6822 | 188.0 | 611 | 0.8967 | 0.6748 |
243
+ | 0.6822 | 188.92 | 614 | 0.8982 | 0.6748 |
244
+ | 0.6822 | 189.85 | 617 | 0.9005 | 0.6748 |
245
+ | 0.6822 | 190.77 | 620 | 0.9020 | 0.6748 |
246
+ | 0.6822 | 192.0 | 624 | 0.9018 | 0.6748 |
247
+ | 0.6822 | 192.92 | 627 | 0.9009 | 0.6748 |
248
+ | 0.6822 | 193.85 | 630 | 0.9002 | 0.6748 |
249
+ | 0.6822 | 194.77 | 633 | 0.8995 | 0.6748 |
250
+ | 0.6822 | 196.0 | 637 | 0.8988 | 0.6748 |
251
+ | 0.6822 | 196.92 | 640 | 0.8973 | 0.6748 |
252
+ | 0.6822 | 197.85 | 643 | 0.8967 | 0.6748 |
253
+ | 0.6822 | 198.77 | 646 | 0.8970 | 0.6748 |
254
+ | 0.6578 | 200.0 | 650 | 0.8954 | 0.6748 |
255
+ | 0.6578 | 200.92 | 653 | 0.8951 | 0.6748 |
256
+ | 0.6578 | 201.85 | 656 | 0.8945 | 0.6748 |
257
+ | 0.6578 | 202.77 | 659 | 0.8946 | 0.6748 |
258
+ | 0.6578 | 204.0 | 663 | 0.8944 | 0.6748 |
259
+ | 0.6578 | 204.92 | 666 | 0.8950 | 0.6748 |
260
+ | 0.6578 | 205.85 | 669 | 0.8960 | 0.6748 |
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+ | 0.6578 | 206.77 | 672 | 0.8969 | 0.6748 |
262
+ | 0.6578 | 208.0 | 676 | 0.8992 | 0.6748 |
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+ | 0.6578 | 208.92 | 679 | 0.8995 | 0.6748 |
264
+ | 0.6578 | 209.85 | 682 | 0.8992 | 0.6748 |
265
+ | 0.6578 | 210.77 | 685 | 0.8990 | 0.6748 |
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+ | 0.6578 | 212.0 | 689 | 0.8986 | 0.6748 |
267
+ | 0.6578 | 212.92 | 692 | 0.8984 | 0.6748 |
268
+ | 0.6578 | 213.85 | 695 | 0.8981 | 0.6748 |
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+ | 0.6578 | 214.77 | 698 | 0.8979 | 0.6748 |
270
+ | 0.6633 | 216.0 | 702 | 0.8977 | 0.6748 |
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+ | 0.6633 | 216.92 | 705 | 0.8973 | 0.6748 |
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+ | 0.6633 | 217.85 | 708 | 0.8968 | 0.6748 |
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+ | 0.6633 | 218.77 | 711 | 0.8963 | 0.6748 |
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+ | 0.6633 | 220.0 | 715 | 0.8957 | 0.6748 |
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+ | 0.6633 | 220.92 | 718 | 0.8955 | 0.6748 |
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+ | 0.6633 | 221.85 | 721 | 0.8952 | 0.6748 |
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+ | 0.6633 | 222.77 | 724 | 0.8954 | 0.6748 |
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+ | 0.6633 | 224.0 | 728 | 0.8953 | 0.6748 |
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+ | 0.6633 | 224.92 | 731 | 0.8952 | 0.6748 |
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+ | 0.6633 | 225.85 | 734 | 0.8952 | 0.6748 |
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+ | 0.6633 | 226.77 | 737 | 0.8951 | 0.6748 |
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+ | 0.6633 | 228.0 | 741 | 0.8949 | 0.6748 |
283
+ | 0.6633 | 228.92 | 744 | 0.8948 | 0.6748 |
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+ | 0.6633 | 229.85 | 747 | 0.8948 | 0.6748 |
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+ | 0.6693 | 230.77 | 750 | 0.8947 | 0.6748 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.0.dev0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.17.1
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+ - Tokenizers 0.15.2
config.json ADDED
@@ -0,0 +1,124 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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