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Teamim-tiny_DropOut-0.5_Augmented_Combined-Data_date-06-07-2024_20-19

Automatic Speech Recognition
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whisper
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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: openai/whisper-tiny
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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-tiny_DropOut-0.5_Augmented_Combined-Data_date-06-07-2024_20-19
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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-tiny_DropOut-0.5_Augmented_Combined-Data_date-06-07-2024_20-19
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+
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+ This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2807
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+ - Wer: 16.7878
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+ - Avg Precision Exact: 0.8378
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+ - Avg Recall Exact: 0.8397
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+ - Avg F1 Exact: 0.8382
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+ - Avg Precision Letter Shift: 0.8599
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+ - Avg Recall Letter Shift: 0.8619
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+ - Avg F1 Letter Shift: 0.8604
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+ - Avg Precision Word Level: 0.8648
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+ - Avg Recall Word Level: 0.8671
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+ - Avg F1 Word Level: 0.8655
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+ - Avg Precision Word Shift: 0.9472
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+ - Avg Recall Word Shift: 0.9510
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+ - Avg F1 Word Shift: 0.9485
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+ - Precision Median Exact: 0.9231
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+ - Recall Median Exact: 0.9231
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+ - F1 Median Exact: 0.9286
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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: 0.0833
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+ - Recall Min Word Shift: 0.0769
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+ - F1 Min Word Shift: 0.08
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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: 8
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+ - eval_batch_size: 32
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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: 1000
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+ - training_steps: 500000
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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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+ | No log | 0.0001 | 1 | 9.1276 | 100.0 | 0.0016 | 0.0166 | 0.0028 | 0.0603 | 0.0627 | 0.0613 | 0.0150 | 0.1274 | 0.0263 | 0.3304 | 0.3453 | 0.3374 | 0.0 | 0.0 | 0.0 | 0.125 | 1.0 | 0.2222 | 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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+ | 0.1478 | 0.5167 | 10000 | 0.2082 | 31.8890 | 0.6951 | 0.7013 | 0.6974 | 0.7292 | 0.7359 | 0.7317 | 0.7377 | 0.7445 | 0.7402 | 0.8718 | 0.8824 | 0.8760 | 0.8 | 0.8 | 0.8 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1 | 0.1 | 0.1000 |
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+ | 0.0557 | 1.0334 | 20000 | 0.1807 | 26.1682 | 0.7472 | 0.7539 | 0.7499 | 0.7761 | 0.7831 | 0.7789 | 0.7827 | 0.7903 | 0.7858 | 0.8946 | 0.9045 | 0.8986 | 0.8462 | 0.8571 | 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 | 0.1538 | 0.1667 | 0.16 |
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+ | 0.0339 | 1.5501 | 30000 | 0.1813 | 24.2204 | 0.7732 | 0.7738 | 0.7729 | 0.8018 | 0.8024 | 0.8014 | 0.8076 | 0.8084 | 0.8073 | 0.9113 | 0.9142 | 0.9118 | 0.875 | 0.875 | 0.875 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0769 | 0.0909 | 0.0833 |
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+ | 0.0206 | 2.0668 | 40000 | 0.1838 | 22.7068 | 0.7804 | 0.7837 | 0.7814 | 0.8073 | 0.8108 | 0.8084 | 0.8133 | 0.8167 | 0.8144 | 0.9158 | 0.9216 | 0.9179 | 0.8889 | 0.9 | 0.8889 | 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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+ | 0.0136 | 2.5834 | 50000 | 0.1874 | 21.5520 | 0.7908 | 0.7923 | 0.7909 | 0.8179 | 0.8195 | 0.8180 | 0.8230 | 0.8249 | 0.8233 | 0.9247 | 0.9283 | 0.9257 | 0.9 | 0.9 | 0.8889 | 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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+ | 0.0296 | 3.1001 | 60000 | 0.1920 | 21.2247 | 0.7969 | 0.7999 | 0.7978 | 0.8213 | 0.8245 | 0.8223 | 0.8270 | 0.8307 | 0.8282 | 0.9244 | 0.9300 | 0.9264 | 0.9 | 0.9 | 0.9 | 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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+ | 0.0147 | 3.6168 | 70000 | 0.2004 | 21.0233 | 0.7936 | 0.7975 | 0.7949 | 0.8210 | 0.8253 | 0.8224 | 0.8270 | 0.8318 | 0.8287 | 0.9278 | 0.9353 | 0.9306 | 0.9 | 0.9091 | 0.9 | 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 | 0.1111 | 0.125 |
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+ | 0.0056 | 4.1335 | 80000 | 0.2070 | 20.3436 | 0.8062 | 0.8047 | 0.8049 | 0.8311 | 0.8296 | 0.8298 | 0.8372 | 0.8362 | 0.8361 | 0.9321 | 0.9335 | 0.9320 | 0.9091 | 0.9091 | 0.9091 | 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 | 0.1111 | 0.125 |
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+ | 0.0059 | 4.6502 | 90000 | 0.2076 | 20.4726 | 0.8049 | 0.8078 | 0.8058 | 0.8309 | 0.8340 | 0.8319 | 0.8365 | 0.8403 | 0.8378 | 0.9279 | 0.9344 | 0.9304 | 0.9091 | 0.9091 | 0.9091 | 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 | 0.125 | 0.1333 |
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+ | 0.0049 | 5.1669 | 100000 | 0.2229 | 20.5198 | 0.8003 | 0.8055 | 0.8024 | 0.8256 | 0.8312 | 0.8278 | 0.8314 | 0.8370 | 0.8336 | 0.9251 | 0.9333 | 0.9284 | 0.9091 | 0.9091 | 0.9 | 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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+ | 0.0065 | 5.6836 | 110000 | 0.2206 | 19.8999 | 0.8084 | 0.8116 | 0.8095 | 0.8332 | 0.8368 | 0.8344 | 0.8390 | 0.8429 | 0.8404 | 0.9307 | 0.9369 | 0.9331 | 0.9091 | 0.9091 | 0.9091 | 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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+ | 0.0024 | 6.2003 | 120000 | 0.2204 | 19.3430 | 0.8114 | 0.8150 | 0.8126 | 0.8360 | 0.8398 | 0.8373 | 0.8414 | 0.8454 | 0.8428 | 0.9331 | 0.9386 | 0.9351 | 0.9091 | 0.9167 | 0.9167 | 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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+ | 0.0046 | 6.7170 | 130000 | 0.2275 | 19.3335 | 0.8185 | 0.8199 | 0.8186 | 0.8430 | 0.8446 | 0.8432 | 0.8485 | 0.8505 | 0.8489 | 0.9337 | 0.9362 | 0.9342 | 0.9167 | 0.9167 | 0.9167 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0909 | 0.0833 | 0.0870 |
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+ | 0.0036 | 7.2336 | 140000 | 0.2297 | 19.3146 | 0.8115 | 0.8142 | 0.8123 | 0.8358 | 0.8390 | 0.8368 | 0.8408 | 0.8441 | 0.8418 | 0.9331 | 0.9375 | 0.9346 | 0.9091 | 0.9091 | 0.9091 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0909 | 0.0714 | 0.0833 |
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+ | 0.0028 | 7.7503 | 150000 | 0.2331 | 19.4846 | 0.8112 | 0.8118 | 0.8110 | 0.8365 | 0.8372 | 0.8363 | 0.8416 | 0.8427 | 0.8416 | 0.9333 | 0.9363 | 0.9340 | 0.9091 | 0.9091 | 0.9091 | 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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+ | 0.003 | 8.2670 | 160000 | 0.2376 | 19.0975 | 0.8109 | 0.8132 | 0.8116 | 0.8345 | 0.8370 | 0.8353 | 0.8403 | 0.8429 | 0.8411 | 0.9360 | 0.9402 | 0.9374 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0038 | 8.7837 | 170000 | 0.2412 | 19.0692 | 0.8147 | 0.8163 | 0.8150 | 0.8395 | 0.8413 | 0.8398 | 0.8453 | 0.8473 | 0.8457 | 0.9358 | 0.9399 | 0.9371 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0013 | 9.3004 | 180000 | 0.2444 | 19.0063 | 0.8123 | 0.8150 | 0.8131 | 0.8363 | 0.8392 | 0.8372 | 0.8420 | 0.8449 | 0.8429 | 0.9355 | 0.9406 | 0.9374 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0028 | 9.8171 | 190000 | 0.2474 | 18.9842 | 0.8139 | 0.8174 | 0.8151 | 0.8381 | 0.8419 | 0.8394 | 0.8437 | 0.8477 | 0.8451 | 0.9352 | 0.9400 | 0.9369 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0029 | 10.3338 | 200000 | 0.2464 | 18.6003 | 0.8203 | 0.8239 | 0.8216 | 0.8449 | 0.8487 | 0.8462 | 0.8504 | 0.8542 | 0.8517 | 0.9384 | 0.9440 | 0.9405 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0008 | 10.8505 | 210000 | 0.2504 | 18.6098 | 0.8180 | 0.8207 | 0.8188 | 0.8413 | 0.8442 | 0.8422 | 0.8463 | 0.8493 | 0.8472 | 0.9376 | 0.9420 | 0.9391 | 0.9167 | 0.9167 | 0.9167 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0909 | 0.1 | 0.0952 |
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+ | 0.0021 | 11.3672 | 220000 | 0.2585 | 18.8363 | 0.8196 | 0.8222 | 0.8204 | 0.8438 | 0.8467 | 0.8447 | 0.8490 | 0.8520 | 0.8499 | 0.9363 | 0.9412 | 0.9381 | 0.9167 | 0.9167 | 0.9167 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0036 | 11.8838 | 230000 | 0.2558 | 18.6916 | 0.8156 | 0.8185 | 0.8165 | 0.8397 | 0.8429 | 0.8407 | 0.8455 | 0.8491 | 0.8467 | 0.9369 | 0.9428 | 0.9392 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0007 | 12.4005 | 240000 | 0.2598 | 18.3077 | 0.8177 | 0.8195 | 0.8181 | 0.8416 | 0.8436 | 0.8421 | 0.8469 | 0.8494 | 0.8476 | 0.9403 | 0.9449 | 0.9419 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0009 | 12.9172 | 250000 | 0.2562 | 18.3549 | 0.8226 | 0.8247 | 0.8232 | 0.8464 | 0.8487 | 0.8471 | 0.8520 | 0.8547 | 0.8528 | 0.9408 | 0.9446 | 0.9421 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0005 | 13.4339 | 260000 | 0.2605 | 18.1598 | 0.8248 | 0.8272 | 0.8255 | 0.8488 | 0.8515 | 0.8497 | 0.8538 | 0.8564 | 0.8546 | 0.9405 | 0.9456 | 0.9424 | 0.9167 | 0.9167 | 0.9167 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0769 | 0.0909 | 0.0833 |
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+ | 0.0015 | 13.9506 | 270000 | 0.2670 | 18.4650 | 0.8204 | 0.8244 | 0.8219 | 0.8445 | 0.8488 | 0.8461 | 0.8494 | 0.8542 | 0.8512 | 0.9368 | 0.9441 | 0.9397 | 0.9167 | 0.9167 | 0.9167 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0833 | 0.0833 |
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+ | 0.0002 | 14.4673 | 280000 | 0.2701 | 19.0094 | 0.8169 | 0.8179 | 0.8168 | 0.8410 | 0.8421 | 0.8409 | 0.8464 | 0.8479 | 0.8466 | 0.9342 | 0.9377 | 0.9353 | 0.9167 | 0.9167 | 0.9167 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.1 | 0.0909 |
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+ | 0.0002 | 14.9840 | 290000 | 0.2699 | 18.2070 | 0.8186 | 0.8239 | 0.8207 | 0.8419 | 0.8475 | 0.8441 | 0.8465 | 0.8523 | 0.8488 | 0.9382 | 0.9456 | 0.9411 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0003 | 15.5007 | 300000 | 0.2696 | 18.4021 | 0.8250 | 0.8248 | 0.8244 | 0.8471 | 0.8470 | 0.8465 | 0.8522 | 0.8528 | 0.8519 | 0.9380 | 0.9412 | 0.9389 | 0.9167 | 0.9167 | 0.9167 | 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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+ | 0.0008 | 16.0174 | 310000 | 0.2645 | 17.6406 | 0.8288 | 0.8314 | 0.8296 | 0.8518 | 0.8546 | 0.8527 | 0.8572 | 0.8602 | 0.8581 | 0.9453 | 0.9498 | 0.9470 | 0.9167 | 0.9231 | 0.9231 | 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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+ | 0.0002 | 16.5340 | 320000 | 0.2712 | 17.8923 | 0.8257 | 0.8290 | 0.8269 | 0.8494 | 0.8529 | 0.8506 | 0.8545 | 0.8581 | 0.8558 | 0.9403 | 0.9458 | 0.9424 | 0.9167 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0833 | 0.0833 |
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+ | 0.0001 | 17.0507 | 330000 | 0.2667 | 17.9710 | 0.8283 | 0.8308 | 0.8291 | 0.8529 | 0.8557 | 0.8538 | 0.8581 | 0.8609 | 0.8590 | 0.9410 | 0.9452 | 0.9425 | 0.9167 | 0.9231 | 0.9231 | 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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+ | 0.0001 | 17.5674 | 340000 | 0.2680 | 17.7130 | 0.8289 | 0.8314 | 0.8296 | 0.8525 | 0.8551 | 0.8532 | 0.8572 | 0.8603 | 0.8582 | 0.9415 | 0.9462 | 0.9432 | 0.9167 | 0.9231 | 0.9231 | 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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+ | 0.0 | 18.0841 | 350000 | 0.2657 | 17.5116 | 0.8328 | 0.8346 | 0.8332 | 0.8559 | 0.8579 | 0.8564 | 0.8607 | 0.8630 | 0.8613 | 0.9429 | 0.9462 | 0.9439 | 0.9231 | 0.9231 | 0.9231 | 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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+ | 0.0008 | 18.6008 | 360000 | 0.2754 | 17.7161 | 0.8339 | 0.8363 | 0.8345 | 0.8568 | 0.8594 | 0.8575 | 0.8620 | 0.8651 | 0.8630 | 0.9425 | 0.9468 | 0.9440 | 0.9167 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0001 | 19.1175 | 370000 | 0.2722 | 17.3007 | 0.8349 | 0.8369 | 0.8354 | 0.8575 | 0.8597 | 0.8581 | 0.8629 | 0.8651 | 0.8635 | 0.9443 | 0.9482 | 0.9456 | 0.9231 | 0.9231 | 0.9231 | 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 |
122
+ | 0.0001 | 19.6342 | 380000 | 0.2751 | 17.2535 | 0.8354 | 0.8383 | 0.8363 | 0.8587 | 0.8618 | 0.8597 | 0.8638 | 0.8670 | 0.8648 | 0.9462 | 0.9506 | 0.9478 | 0.9231 | 0.9231 | 0.9231 | 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 | 0.125 | 0.1333 |
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+ | 0.0 | 20.1509 | 390000 | 0.2743 | 17.3574 | 0.8317 | 0.8351 | 0.8329 | 0.8552 | 0.8586 | 0.8564 | 0.8601 | 0.8638 | 0.8613 | 0.9449 | 0.9500 | 0.9468 | 0.9167 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 20.6676 | 400000 | 0.2794 | 17.5367 | 0.8343 | 0.8347 | 0.8340 | 0.8574 | 0.8579 | 0.8571 | 0.8624 | 0.8632 | 0.8622 | 0.9442 | 0.9465 | 0.9447 | 0.9231 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0833 | 0.0833 |
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+ | 0.0 | 21.1843 | 410000 | 0.2782 | 17.1717 | 0.8365 | 0.8367 | 0.8361 | 0.8591 | 0.8593 | 0.8586 | 0.8640 | 0.8646 | 0.8637 | 0.9457 | 0.9481 | 0.9463 | 0.9231 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0833 | 0.0833 |
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+ | 0.0 | 21.7009 | 420000 | 0.2778 | 17.1308 | 0.8358 | 0.8379 | 0.8363 | 0.8590 | 0.8612 | 0.8596 | 0.8641 | 0.8664 | 0.8647 | 0.9451 | 0.9491 | 0.9465 | 0.9231 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 22.2176 | 430000 | 0.2785 | 17.0553 | 0.8366 | 0.8386 | 0.8371 | 0.8590 | 0.8612 | 0.8596 | 0.8640 | 0.8663 | 0.8646 | 0.9456 | 0.9493 | 0.9469 | 0.9231 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 22.7343 | 440000 | 0.2808 | 17.0679 | 0.8365 | 0.8380 | 0.8368 | 0.8592 | 0.8608 | 0.8595 | 0.8639 | 0.8659 | 0.8644 | 0.9457 | 0.9498 | 0.9472 | 0.9231 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 23.2510 | 450000 | 0.2794 | 16.8885 | 0.8352 | 0.8375 | 0.8359 | 0.8572 | 0.8596 | 0.8579 | 0.8622 | 0.8648 | 0.8630 | 0.9470 | 0.9512 | 0.9485 | 0.9231 | 0.9231 | 0.9231 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 23.7677 | 460000 | 0.2795 | 16.9514 | 0.8374 | 0.8384 | 0.8374 | 0.8593 | 0.8604 | 0.8593 | 0.8645 | 0.8657 | 0.8646 | 0.9470 | 0.9498 | 0.9478 | 0.9231 | 0.9231 | 0.9286 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 24.2844 | 470000 | 0.2806 | 16.9452 | 0.8385 | 0.8403 | 0.8390 | 0.8609 | 0.8628 | 0.8613 | 0.8657 | 0.8679 | 0.8663 | 0.9468 | 0.9505 | 0.9481 | 0.9231 | 0.9231 | 0.9286 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 24.8011 | 480000 | 0.2804 | 16.7784 | 0.8385 | 0.8403 | 0.8389 | 0.8605 | 0.8624 | 0.8610 | 0.8653 | 0.8675 | 0.8659 | 0.9473 | 0.9510 | 0.9486 | 0.9231 | 0.9231 | 0.9286 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 25.3178 | 490000 | 0.2806 | 16.8098 | 0.8376 | 0.8395 | 0.8381 | 0.8596 | 0.8616 | 0.8601 | 0.8644 | 0.8667 | 0.8651 | 0.9472 | 0.9511 | 0.9486 | 0.9231 | 0.9231 | 0.9286 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
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+ | 0.0 | 25.8345 | 500000 | 0.2807 | 16.7878 | 0.8378 | 0.8397 | 0.8382 | 0.8599 | 0.8619 | 0.8604 | 0.8648 | 0.8671 | 0.8655 | 0.9472 | 0.9510 | 0.9485 | 0.9231 | 0.9231 | 0.9286 | 1.0 | 1.0 | 1.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0833 | 0.0769 | 0.08 |
135
+
136
+
137
+ ### Framework versions
138
+
139
+ - Transformers 4.41.2
140
+ - Pytorch 2.2.1
141
+ - Datasets 2.20.0
142
+ - Tokenizers 0.19.1
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