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cantillation
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Teamim-medium_Random_WeightDecay-0.005_Augmented_New-Data_date-11-03-2025

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Hebrew
whisper
hf-asr-leaderboard
Generated from Trainer
Model card Files Metrics Community
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  1. README.md +112 -0
  2. generation_config.json +248 -0
  3. model.safetensors +1 -1
  4. runs/Mar11_13-18-32_hetro232/events.out.tfevents.1741691915.hetro232 +2 -2
README.md ADDED
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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: openai/whisper-medium
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: Teamim-medium_Random_WeightDecay-0.005_Augmented_New-Data_date-11-03-2025
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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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+ # Teamim-medium_Random_WeightDecay-0.005_Augmented_New-Data_date-11-03-2025
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+
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+ This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1124
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+ - Wer: 16.7836
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+ - Avg Precision Exact: 0.7079
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+ - Avg Recall Exact: 0.7184
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+ - Avg F1 Exact: 0.7126
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+ - Avg Precision Letter Shift: 0.7171
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+ - Avg Recall Letter Shift: 0.7274
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+ - Avg F1 Letter Shift: 0.7218
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+ - Avg Precision Word Level: 0.7192
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+ - Avg Recall Word Level: 0.7284
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+ - Avg F1 Word Level: 0.7233
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+ - Avg Precision Word Shift: 0.8626
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+ - Avg Recall Word Shift: 0.8745
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+ - Avg F1 Word Shift: 0.8680
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+ - Precision Median Exact: 0.8462
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+ - Recall Median Exact: 0.875
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+ - F1 Median Exact: 0.8571
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+ - Precision Max Exact: 1.0
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+ - Recall Max Exact: 1.0
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+ - F1 Max Exact: 1.0
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+ - Precision Min Exact: 0.0
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+ - Recall Min Exact: 0.0
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+ - F1 Min Exact: 0.0
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+ - Precision Min Letter Shift: 0.0
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+ - Recall Min Letter Shift: 0.0
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+ - F1 Min Letter Shift: 0.0
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+ - Precision Min Word Level: 0.0
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+ - Recall Min Word Level: 0.0
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+ - F1 Min Word Level: 0.0
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+ - Precision Min Word Shift: 0.1905
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+ - Recall Min Word Shift: 0.1379
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+ - F1 Min Word Shift: 0.16
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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: 1e-05
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+ - train_batch_size: 16
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - lr_scheduler_warmup_steps: 500
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+ - training_steps: 2000
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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 | Wer | Avg Precision Exact | Avg Recall Exact | Avg F1 Exact | Avg Precision Letter Shift | Avg Recall Letter Shift | Avg F1 Letter Shift | Avg Precision Word Level | Avg Recall Word Level | Avg F1 Word Level | Avg Precision Word Shift | Avg Recall Word Shift | Avg F1 Word Shift | Precision Median Exact | Recall Median Exact | F1 Median Exact | Precision Max Exact | Recall Max Exact | F1 Max Exact | Precision Min Exact | Recall Min Exact | F1 Min Exact | Precision Min Letter Shift | Recall Min Letter Shift | F1 Min Letter Shift | Precision Min Word Level | Recall Min Word Level | F1 Min Word Level | Precision Min Word Shift | Recall Min Word Shift | F1 Min Word Shift |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|:----------------------:|:-------------------:|:---------------:|:-------------------:|:----------------:|:------------:|:-------------------:|:----------------:|:------------:|:--------------------------:|:-----------------------:|:-------------------:|:------------------------:|:---------------------:|:-----------------:|:------------------------:|:---------------------:|:-----------------:|
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+ | 3.4502 | 0.0620 | 100 | 3.2430 | 104.9708 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
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+ | 1.9915 | 0.1240 | 200 | 1.7908 | 96.0234 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
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+ | 0.9248 | 0.1860 | 300 | 0.9288 | 88.7719 | 0.0665 | 0.0821 | 0.0731 | 0.1071 | 0.1322 | 0.1177 | 0.1421 | 0.1783 | 0.1566 | 0.3138 | 0.4886 | 0.3797 | 0.0476 | 0.0670 | 0.0533 | 0.2353 | 0.25 | 0.2424 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0690 | 0.1538 | 0.0952 |
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+ | 0.7969 | 0.2480 | 400 | 0.7450 | 82.8070 | 0.1028 | 0.1150 | 0.1082 | 0.1212 | 0.1350 | 0.1272 | 0.1472 | 0.1617 | 0.1536 | 0.3450 | 0.4150 | 0.3756 | 0.0889 | 0.0952 | 0.0910 | 0.3333 | 0.3636 | 0.3478 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1034 | 0.2 | 0.1463 |
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+ | 0.5336 | 0.3100 | 500 | 0.5601 | 65.5556 | 0.2327 | 0.2448 | 0.2380 | 0.2511 | 0.2643 | 0.2569 | 0.2669 | 0.2784 | 0.2720 | 0.4687 | 0.4993 | 0.4824 | 0.1909 | 0.2 | 0.1861 | 0.6522 | 0.75 | 0.6977 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1034 | 0.12 | 0.1111 |
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+ | 0.4365 | 0.3720 | 600 | 0.4365 | 55.0877 | 0.3414 | 0.3479 | 0.3432 | 0.3593 | 0.3657 | 0.3610 | 0.3678 | 0.3719 | 0.3685 | 0.5642 | 0.5763 | 0.5683 | 0.3455 | 0.3514 | 0.3452 | 0.8333 | 0.8947 | 0.8205 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1538 | 0.1481 | 0.1569 |
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+ | 0.3218 | 0.4340 | 700 | 0.3385 | 43.3918 | 0.4119 | 0.4124 | 0.4107 | 0.4270 | 0.4274 | 0.4257 | 0.4327 | 0.4317 | 0.4307 | 0.6591 | 0.6671 | 0.6609 | 0.47 | 0.4451 | 0.4726 | 0.9130 | 0.9130 | 0.9130 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.2674 | 0.4960 | 800 | 0.2900 | 36.7251 | 0.4593 | 0.4809 | 0.4693 | 0.4761 | 0.4979 | 0.4861 | 0.4828 | 0.5013 | 0.4913 | 0.7063 | 0.7348 | 0.7193 | 0.5339 | 0.5683 | 0.5499 | 0.88 | 0.9091 | 0.8889 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.16 | 0.1481 | 0.1538 |
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+ | 0.2435 | 0.5580 | 900 | 0.2485 | 32.5146 | 0.5049 | 0.5190 | 0.5112 | 0.5159 | 0.5296 | 0.5220 | 0.5243 | 0.5339 | 0.5284 | 0.7363 | 0.7548 | 0.7446 | 0.6243 | 0.6519 | 0.6389 | 1.0 | 0.96 | 0.9796 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1154 | 0.125 | 0.1200 |
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+ | 0.224 | 0.6200 | 1000 | 0.2299 | 32.9240 | 0.5286 | 0.5464 | 0.5368 | 0.5444 | 0.5625 | 0.5527 | 0.5520 | 0.5676 | 0.5592 | 0.7225 | 0.7469 | 0.7338 | 0.6190 | 0.6795 | 0.6373 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.1796 | 0.6820 | 1100 | 0.2040 | 29.7661 | 0.5553 | 0.5672 | 0.5607 | 0.5683 | 0.5801 | 0.5736 | 0.5697 | 0.5813 | 0.5749 | 0.7460 | 0.7575 | 0.7510 | 0.6812 | 0.7050 | 0.6874 | 0.96 | 0.96 | 0.96 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
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+ | 0.1939 | 0.7440 | 1200 | 0.1875 | 27.2515 | 0.5642 | 0.5779 | 0.5704 | 0.5769 | 0.5905 | 0.5830 | 0.5832 | 0.5957 | 0.5888 | 0.7925 | 0.8085 | 0.7995 | 0.7042 | 0.7434 | 0.7226 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1905 | 0.1538 | 0.1702 |
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+ | 0.1782 | 0.8060 | 1300 | 0.1636 | 23.5088 | 0.6170 | 0.6291 | 0.6225 | 0.6296 | 0.6410 | 0.6348 | 0.6339 | 0.6444 | 0.6386 | 0.8149 | 0.8309 | 0.8221 | 0.75 | 0.7777 | 0.7693 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2273 | 0.1786 | 0.2 |
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+ | 0.1506 | 0.8679 | 1400 | 0.1518 | 22.0468 | 0.6372 | 0.6535 | 0.6448 | 0.6466 | 0.6629 | 0.6543 | 0.6490 | 0.6634 | 0.6557 | 0.8046 | 0.8217 | 0.8125 | 0.7722 | 0.7906 | 0.7852 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.08 | 0.0690 | 0.0741 |
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+ | 0.1519 | 0.9299 | 1500 | 0.1401 | 21.5789 | 0.6278 | 0.6357 | 0.6313 | 0.6379 | 0.6459 | 0.6414 | 0.6397 | 0.6464 | 0.6426 | 0.8312 | 0.8386 | 0.8342 | 0.7723 | 0.7906 | 0.7804 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1 | 0.1176 |
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+ | 0.1225 | 0.9919 | 1600 | 0.1369 | 20.7602 | 0.6510 | 0.6670 | 0.6585 | 0.6575 | 0.6735 | 0.6650 | 0.6614 | 0.6748 | 0.6676 | 0.8227 | 0.8404 | 0.8308 | 0.8038 | 0.8153 | 0.8048 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1429 | 0.1034 | 0.1200 |
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+ | 0.1061 | 1.0539 | 1700 | 0.1262 | 19.2398 | 0.6681 | 0.6774 | 0.6723 | 0.6741 | 0.6835 | 0.6784 | 0.6760 | 0.6838 | 0.6795 | 0.8333 | 0.8404 | 0.8361 | 0.8333 | 0.8596 | 0.8486 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.04 | 0.0370 | 0.0385 |
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+ | 0.1094 | 1.1159 | 1800 | 0.1188 | 17.0760 | 0.7152 | 0.7275 | 0.7209 | 0.7229 | 0.7354 | 0.7287 | 0.7265 | 0.7375 | 0.7315 | 0.8590 | 0.8730 | 0.8654 | 0.8394 | 0.8652 | 0.8478 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1905 | 0.1333 | 0.1569 |
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+ | 0.1039 | 1.1779 | 1900 | 0.1142 | 17.2515 | 0.7024 | 0.7137 | 0.7075 | 0.7137 | 0.7247 | 0.7186 | 0.7160 | 0.7256 | 0.7202 | 0.8636 | 0.8739 | 0.8681 | 0.84 | 0.8652 | 0.8518 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.2727 | 0.2143 | 0.2400 |
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+ | 0.093 | 1.2399 | 2000 | 0.1124 | 16.7836 | 0.7079 | 0.7184 | 0.7126 | 0.7171 | 0.7274 | 0.7218 | 0.7192 | 0.7284 | 0.7233 | 0.8626 | 0.8745 | 0.8680 | 0.8462 | 0.875 | 0.8571 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1905 | 0.1379 | 0.16 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.49.0
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+ - Pytorch 2.6.0+cu126
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+ - Datasets 2.12.0
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+ - Tokenizers 0.20.1
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