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hubert-classifier-aug-fold-2

Audio Classification
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hubert
Generated from Trainer
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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: facebook/hubert-base-ls960
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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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+ - precision
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+ - recall
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+ - f1
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+ model-index:
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+ - name: hubert-classifier-aug-fold-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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+ # hubert-classifier-aug-fold-2
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+
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+ This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.7004
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+ - Accuracy: 0.8895
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+ - Precision: 0.9016
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+ - Recall: 0.8895
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+ - F1: 0.8901
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+ - Binary: 0.9228
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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: 32
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+ - eval_batch_size: 32
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 128
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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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+ - num_epochs: 30
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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 | Precision | Recall | F1 | Binary |
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+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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+ | No log | 0.13 | 50 | 3.8323 | 0.0877 | 0.0522 | 0.0877 | 0.0397 | 0.3479 |
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+ | No log | 0.27 | 100 | 3.2624 | 0.1808 | 0.1370 | 0.1808 | 0.1221 | 0.4188 |
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+ | No log | 0.4 | 150 | 2.8729 | 0.2955 | 0.2056 | 0.2955 | 0.2056 | 0.5031 |
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+ | No log | 0.54 | 200 | 2.3928 | 0.4157 | 0.3408 | 0.4157 | 0.3318 | 0.5904 |
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+ | No log | 0.67 | 250 | 2.0739 | 0.4548 | 0.4212 | 0.4548 | 0.3875 | 0.6186 |
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+ | No log | 0.81 | 300 | 1.7722 | 0.5547 | 0.5132 | 0.5547 | 0.4923 | 0.6887 |
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+ | No log | 0.94 | 350 | 1.5220 | 0.5951 | 0.5844 | 0.5951 | 0.5489 | 0.7157 |
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+ | 2.8578 | 1.08 | 400 | 1.4062 | 0.6154 | 0.5903 | 0.6154 | 0.5690 | 0.7301 |
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+ | 2.8578 | 1.21 | 450 | 1.1712 | 0.7126 | 0.7203 | 0.7126 | 0.6873 | 0.7978 |
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+ | 2.8578 | 1.35 | 500 | 1.0957 | 0.6815 | 0.6716 | 0.6815 | 0.6441 | 0.7764 |
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+ | 2.8578 | 1.48 | 550 | 1.0095 | 0.7395 | 0.7600 | 0.7395 | 0.7227 | 0.8165 |
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+ | 2.8578 | 1.62 | 600 | 0.9283 | 0.7571 | 0.7774 | 0.7571 | 0.7454 | 0.8301 |
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+ | 2.8578 | 1.75 | 650 | 0.9876 | 0.7544 | 0.7818 | 0.7544 | 0.7451 | 0.8270 |
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+ | 2.8578 | 1.89 | 700 | 0.7728 | 0.8016 | 0.8095 | 0.8016 | 0.7934 | 0.8601 |
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+ | 1.2835 | 2.02 | 750 | 0.8472 | 0.7827 | 0.7946 | 0.7827 | 0.7714 | 0.8457 |
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+ | 1.2835 | 2.16 | 800 | 0.7331 | 0.7989 | 0.8183 | 0.7989 | 0.7962 | 0.8575 |
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+ | 1.2835 | 2.29 | 850 | 0.8126 | 0.7814 | 0.7986 | 0.7814 | 0.7745 | 0.8441 |
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+ | 1.2835 | 2.43 | 900 | 0.7898 | 0.7814 | 0.8120 | 0.7814 | 0.7749 | 0.8463 |
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+ | 1.2835 | 2.56 | 950 | 0.7014 | 0.8111 | 0.8311 | 0.8111 | 0.8082 | 0.8671 |
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+ | 1.2835 | 2.7 | 1000 | 0.6225 | 0.8300 | 0.8532 | 0.8300 | 0.8277 | 0.8808 |
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+ | 1.2835 | 2.83 | 1050 | 0.7096 | 0.8178 | 0.8356 | 0.8178 | 0.8155 | 0.8715 |
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+ | 1.2835 | 2.96 | 1100 | 0.6304 | 0.8232 | 0.8458 | 0.8232 | 0.8202 | 0.8773 |
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+ | 0.8295 | 3.1 | 1150 | 0.5950 | 0.8435 | 0.8601 | 0.8435 | 0.8428 | 0.8907 |
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+ | 0.8295 | 3.23 | 1200 | 0.6140 | 0.8421 | 0.8579 | 0.8421 | 0.8410 | 0.8892 |
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+ | 0.8295 | 3.37 | 1250 | 0.6443 | 0.8327 | 0.8578 | 0.8327 | 0.8293 | 0.8826 |
87
+ | 0.8295 | 3.5 | 1300 | 0.6662 | 0.8205 | 0.8456 | 0.8205 | 0.8158 | 0.8737 |
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+ | 0.8295 | 3.64 | 1350 | 0.6056 | 0.8502 | 0.8638 | 0.8502 | 0.8483 | 0.8949 |
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+ | 0.8295 | 3.77 | 1400 | 0.5968 | 0.8448 | 0.8591 | 0.8448 | 0.8421 | 0.8907 |
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+ | 0.8295 | 3.91 | 1450 | 0.5734 | 0.8354 | 0.8542 | 0.8354 | 0.8329 | 0.8845 |
91
+ | 0.6277 | 4.04 | 1500 | 0.6580 | 0.8340 | 0.8521 | 0.8340 | 0.8331 | 0.8830 |
92
+ | 0.6277 | 4.18 | 1550 | 0.6149 | 0.8529 | 0.8664 | 0.8529 | 0.8523 | 0.8981 |
93
+ | 0.6277 | 4.31 | 1600 | 0.5965 | 0.8556 | 0.8715 | 0.8556 | 0.8536 | 0.8978 |
94
+ | 0.6277 | 4.45 | 1650 | 0.5801 | 0.8570 | 0.8749 | 0.8570 | 0.8554 | 0.8996 |
95
+ | 0.6277 | 4.58 | 1700 | 0.6019 | 0.8516 | 0.8679 | 0.8516 | 0.8502 | 0.8960 |
96
+ | 0.6277 | 4.72 | 1750 | 0.6178 | 0.8502 | 0.8643 | 0.8502 | 0.8488 | 0.8937 |
97
+ | 0.6277 | 4.85 | 1800 | 0.5726 | 0.8637 | 0.8790 | 0.8637 | 0.8627 | 0.9059 |
98
+ | 0.6277 | 4.99 | 1850 | 0.5581 | 0.8596 | 0.8751 | 0.8596 | 0.8577 | 0.9020 |
99
+ | 0.5166 | 5.12 | 1900 | 0.6064 | 0.8448 | 0.8649 | 0.8448 | 0.8424 | 0.8907 |
100
+ | 0.5166 | 5.26 | 1950 | 0.6728 | 0.8516 | 0.8728 | 0.8516 | 0.8502 | 0.8958 |
101
+ | 0.5166 | 5.39 | 2000 | 0.5952 | 0.8650 | 0.8818 | 0.8650 | 0.8652 | 0.9067 |
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+ | 0.5166 | 5.53 | 2050 | 0.4922 | 0.8704 | 0.8900 | 0.8704 | 0.8700 | 0.9100 |
103
+ | 0.5166 | 5.66 | 2100 | 0.5558 | 0.8812 | 0.8954 | 0.8812 | 0.8817 | 0.9165 |
104
+ | 0.5166 | 5.8 | 2150 | 0.6257 | 0.8596 | 0.8778 | 0.8596 | 0.8602 | 0.9030 |
105
+ | 0.5166 | 5.93 | 2200 | 0.5901 | 0.8650 | 0.8839 | 0.8650 | 0.8654 | 0.9054 |
106
+ | 0.4409 | 6.06 | 2250 | 0.5639 | 0.8650 | 0.8765 | 0.8650 | 0.8642 | 0.9050 |
107
+ | 0.4409 | 6.2 | 2300 | 0.5967 | 0.8610 | 0.8793 | 0.8610 | 0.8582 | 0.9022 |
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+ | 0.4409 | 6.33 | 2350 | 0.5664 | 0.8704 | 0.8856 | 0.8704 | 0.8703 | 0.9086 |
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+ | 0.4409 | 6.47 | 2400 | 0.5706 | 0.8745 | 0.8885 | 0.8745 | 0.8742 | 0.9119 |
110
+ | 0.4409 | 6.6 | 2450 | 0.5945 | 0.8637 | 0.8768 | 0.8637 | 0.8623 | 0.9039 |
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+ | 0.4409 | 6.74 | 2500 | 0.6792 | 0.8556 | 0.8722 | 0.8556 | 0.8526 | 0.8973 |
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+ | 0.4409 | 6.87 | 2550 | 0.6265 | 0.8623 | 0.8788 | 0.8623 | 0.8612 | 0.9038 |
113
+ | 0.3941 | 7.01 | 2600 | 0.5768 | 0.8691 | 0.8845 | 0.8691 | 0.8682 | 0.9090 |
114
+ | 0.3941 | 7.14 | 2650 | 0.5951 | 0.8610 | 0.8797 | 0.8610 | 0.8588 | 0.9039 |
115
+ | 0.3941 | 7.28 | 2700 | 0.6621 | 0.8596 | 0.8728 | 0.8596 | 0.8570 | 0.9008 |
116
+ | 0.3941 | 7.41 | 2750 | 0.5764 | 0.8745 | 0.8876 | 0.8745 | 0.8745 | 0.9128 |
117
+ | 0.3941 | 7.55 | 2800 | 0.6080 | 0.8677 | 0.8830 | 0.8677 | 0.8669 | 0.9067 |
118
+ | 0.3941 | 7.68 | 2850 | 0.6498 | 0.8691 | 0.8831 | 0.8691 | 0.8675 | 0.9086 |
119
+ | 0.3941 | 7.82 | 2900 | 0.6737 | 0.8475 | 0.8641 | 0.8475 | 0.8446 | 0.8928 |
120
+ | 0.3941 | 7.95 | 2950 | 0.7467 | 0.8462 | 0.8669 | 0.8462 | 0.8434 | 0.8926 |
121
+ | 0.3567 | 8.09 | 3000 | 0.5592 | 0.8745 | 0.8897 | 0.8745 | 0.8744 | 0.9117 |
122
+ | 0.3567 | 8.22 | 3050 | 0.5933 | 0.8772 | 0.8913 | 0.8772 | 0.8764 | 0.9128 |
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+ | 0.3567 | 8.36 | 3100 | 0.5294 | 0.8826 | 0.8931 | 0.8826 | 0.8797 | 0.9171 |
124
+ | 0.3567 | 8.49 | 3150 | 0.6415 | 0.8664 | 0.8803 | 0.8664 | 0.8647 | 0.9062 |
125
+ | 0.3567 | 8.63 | 3200 | 0.6076 | 0.8704 | 0.8862 | 0.8704 | 0.8694 | 0.9085 |
126
+ | 0.3567 | 8.76 | 3250 | 0.5787 | 0.8812 | 0.8963 | 0.8812 | 0.8802 | 0.9171 |
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+ | 0.3567 | 8.89 | 3300 | 0.5419 | 0.8799 | 0.8909 | 0.8799 | 0.8789 | 0.9161 |
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+ | 0.3207 | 9.03 | 3350 | 0.5635 | 0.8731 | 0.8837 | 0.8731 | 0.8702 | 0.9108 |
129
+ | 0.3207 | 9.16 | 3400 | 0.5488 | 0.8839 | 0.8959 | 0.8839 | 0.8826 | 0.9182 |
130
+ | 0.3207 | 9.3 | 3450 | 0.5245 | 0.8839 | 0.8974 | 0.8839 | 0.8834 | 0.9185 |
131
+ | 0.3207 | 9.43 | 3500 | 0.6777 | 0.8637 | 0.8780 | 0.8637 | 0.8615 | 0.9038 |
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+ | 0.3207 | 9.57 | 3550 | 0.6236 | 0.8704 | 0.8888 | 0.8704 | 0.8678 | 0.9081 |
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+ | 0.3207 | 9.7 | 3600 | 0.6140 | 0.8718 | 0.8865 | 0.8718 | 0.8714 | 0.9111 |
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+ | 0.3207 | 9.84 | 3650 | 0.6249 | 0.8623 | 0.8718 | 0.8623 | 0.8593 | 0.9040 |
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+ | 0.3207 | 9.97 | 3700 | 0.5656 | 0.8772 | 0.8874 | 0.8772 | 0.8757 | 0.9138 |
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+ | 0.3047 | 10.11 | 3750 | 0.6042 | 0.8731 | 0.8821 | 0.8731 | 0.8709 | 0.9109 |
137
+ | 0.3047 | 10.24 | 3800 | 0.5685 | 0.8826 | 0.8921 | 0.8826 | 0.8823 | 0.9170 |
138
+ | 0.3047 | 10.38 | 3850 | 0.6586 | 0.8758 | 0.8885 | 0.8758 | 0.8742 | 0.9135 |
139
+ | 0.3047 | 10.51 | 3900 | 0.6546 | 0.8758 | 0.8877 | 0.8758 | 0.8743 | 0.9124 |
140
+ | 0.3047 | 10.65 | 3950 | 0.6802 | 0.8677 | 0.8796 | 0.8677 | 0.8652 | 0.9076 |
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+ | 0.3047 | 10.78 | 4000 | 0.6282 | 0.8799 | 0.8937 | 0.8799 | 0.8785 | 0.9166 |
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+ | 0.3047 | 10.92 | 4050 | 0.6671 | 0.8677 | 0.8830 | 0.8677 | 0.8663 | 0.9072 |
143
+ | 0.2817 | 11.05 | 4100 | 0.5854 | 0.8812 | 0.8957 | 0.8812 | 0.8797 | 0.9166 |
144
+ | 0.2817 | 11.19 | 4150 | 0.6261 | 0.8758 | 0.8887 | 0.8758 | 0.8740 | 0.9132 |
145
+ | 0.2817 | 11.32 | 4200 | 0.6103 | 0.8799 | 0.8949 | 0.8799 | 0.8790 | 0.9165 |
146
+ | 0.2817 | 11.46 | 4250 | 0.5799 | 0.8799 | 0.8893 | 0.8799 | 0.8781 | 0.9161 |
147
+ | 0.2817 | 11.59 | 4300 | 0.5591 | 0.8866 | 0.8985 | 0.8866 | 0.8865 | 0.9212 |
148
+ | 0.2817 | 11.73 | 4350 | 0.5359 | 0.8893 | 0.9010 | 0.8893 | 0.8892 | 0.9231 |
149
+ | 0.2817 | 11.86 | 4400 | 0.6664 | 0.8677 | 0.8811 | 0.8677 | 0.8674 | 0.9076 |
150
+ | 0.2817 | 11.99 | 4450 | 0.6034 | 0.8799 | 0.8923 | 0.8799 | 0.8799 | 0.9159 |
151
+ | 0.2736 | 12.13 | 4500 | 0.6436 | 0.8745 | 0.8873 | 0.8745 | 0.8722 | 0.9113 |
152
+ | 0.2736 | 12.26 | 4550 | 0.6724 | 0.8799 | 0.8963 | 0.8799 | 0.8792 | 0.9161 |
153
+ | 0.2736 | 12.4 | 4600 | 0.5840 | 0.8893 | 0.9005 | 0.8893 | 0.8886 | 0.9227 |
154
+ | 0.2736 | 12.53 | 4650 | 0.6570 | 0.8785 | 0.8918 | 0.8785 | 0.8779 | 0.9151 |
155
+ | 0.2736 | 12.67 | 4700 | 0.6322 | 0.8745 | 0.8877 | 0.8745 | 0.8737 | 0.9119 |
156
+ | 0.2736 | 12.8 | 4750 | 0.6748 | 0.8880 | 0.9002 | 0.8880 | 0.8878 | 0.9212 |
157
+ | 0.2736 | 12.94 | 4800 | 0.7166 | 0.8718 | 0.8864 | 0.8718 | 0.8695 | 0.9105 |
158
+ | 0.2541 | 13.07 | 4850 | 0.5717 | 0.8866 | 0.9001 | 0.8866 | 0.8858 | 0.9198 |
159
+ | 0.2541 | 13.21 | 4900 | 0.6211 | 0.8745 | 0.8910 | 0.8745 | 0.8735 | 0.9123 |
160
+ | 0.2541 | 13.34 | 4950 | 0.5923 | 0.8799 | 0.8975 | 0.8799 | 0.8805 | 0.9151 |
161
+ | 0.2541 | 13.48 | 5000 | 0.5885 | 0.8758 | 0.8891 | 0.8758 | 0.8759 | 0.9132 |
162
+ | 0.2541 | 13.61 | 5050 | 0.6245 | 0.8866 | 0.8998 | 0.8866 | 0.8862 | 0.9192 |
163
+ | 0.2541 | 13.75 | 5100 | 0.6897 | 0.8718 | 0.8866 | 0.8718 | 0.8706 | 0.9090 |
164
+ | 0.2541 | 13.88 | 5150 | 0.6919 | 0.8677 | 0.8807 | 0.8677 | 0.8677 | 0.9076 |
165
+ | 0.2384 | 14.02 | 5200 | 0.5996 | 0.8961 | 0.9079 | 0.8961 | 0.8951 | 0.9269 |
166
+ | 0.2384 | 14.15 | 5250 | 0.6649 | 0.8880 | 0.9013 | 0.8880 | 0.8861 | 0.9208 |
167
+ | 0.2384 | 14.29 | 5300 | 0.7136 | 0.8664 | 0.8854 | 0.8664 | 0.8625 | 0.9061 |
168
+ | 0.2384 | 14.42 | 5350 | 0.6670 | 0.8812 | 0.8970 | 0.8812 | 0.8812 | 0.9158 |
169
+ | 0.2384 | 14.56 | 5400 | 0.6286 | 0.8826 | 0.8952 | 0.8826 | 0.8820 | 0.9175 |
170
+ | 0.2384 | 14.69 | 5450 | 0.6297 | 0.8785 | 0.8877 | 0.8785 | 0.8755 | 0.9151 |
171
+ | 0.2384 | 14.82 | 5500 | 0.7010 | 0.8799 | 0.8953 | 0.8799 | 0.8795 | 0.9159 |
172
+ | 0.2384 | 14.96 | 5550 | 0.6078 | 0.8853 | 0.8985 | 0.8853 | 0.8822 | 0.9197 |
173
+ | 0.2218 | 15.09 | 5600 | 0.6684 | 0.8758 | 0.8917 | 0.8758 | 0.8751 | 0.9127 |
174
+ | 0.2218 | 15.23 | 5650 | 0.6672 | 0.8799 | 0.8917 | 0.8799 | 0.8774 | 0.9157 |
175
+ | 0.2218 | 15.36 | 5700 | 0.6440 | 0.8839 | 0.8998 | 0.8839 | 0.8828 | 0.9189 |
176
+ | 0.2218 | 15.5 | 5750 | 0.6807 | 0.8866 | 0.9002 | 0.8866 | 0.8863 | 0.9204 |
177
+ | 0.2218 | 15.63 | 5800 | 0.6325 | 0.8839 | 0.8949 | 0.8839 | 0.8831 | 0.9184 |
178
+ | 0.2218 | 15.77 | 5850 | 0.6078 | 0.8934 | 0.9046 | 0.8934 | 0.8918 | 0.9250 |
179
+ | 0.2218 | 15.9 | 5900 | 0.6638 | 0.8866 | 0.9005 | 0.8866 | 0.8860 | 0.9202 |
180
+ | 0.2192 | 16.04 | 5950 | 0.5822 | 0.8920 | 0.9044 | 0.8920 | 0.8910 | 0.9240 |
181
+ | 0.2192 | 16.17 | 6000 | 0.6028 | 0.8785 | 0.8922 | 0.8785 | 0.8765 | 0.9138 |
182
+ | 0.2192 | 16.31 | 6050 | 0.6012 | 0.8893 | 0.9013 | 0.8893 | 0.8884 | 0.9227 |
183
+ | 0.2192 | 16.44 | 6100 | 0.5819 | 0.8853 | 0.8980 | 0.8853 | 0.8838 | 0.9193 |
184
+ | 0.2192 | 16.58 | 6150 | 0.6055 | 0.8826 | 0.8998 | 0.8826 | 0.8818 | 0.9170 |
185
+ | 0.2192 | 16.71 | 6200 | 0.6642 | 0.9001 | 0.9123 | 0.9001 | 0.8991 | 0.9297 |
186
+ | 0.2192 | 16.85 | 6250 | 0.6235 | 0.8880 | 0.8976 | 0.8880 | 0.8857 | 0.9219 |
187
+ | 0.2192 | 16.98 | 6300 | 0.5460 | 0.8920 | 0.9007 | 0.8920 | 0.8905 | 0.9240 |
188
+ | 0.2103 | 17.12 | 6350 | 0.5525 | 0.8920 | 0.9031 | 0.8920 | 0.8908 | 0.9242 |
189
+ | 0.2103 | 17.25 | 6400 | 0.5847 | 0.8974 | 0.9092 | 0.8974 | 0.8960 | 0.9279 |
190
+ | 0.2103 | 17.39 | 6450 | 0.5585 | 0.8961 | 0.9081 | 0.8961 | 0.8958 | 0.9260 |
191
+ | 0.2103 | 17.52 | 6500 | 0.5424 | 0.8920 | 0.9008 | 0.8920 | 0.8911 | 0.9247 |
192
+ | 0.2103 | 17.65 | 6550 | 0.5473 | 0.9042 | 0.9141 | 0.9042 | 0.9032 | 0.9331 |
193
+ | 0.2103 | 17.79 | 6600 | 0.5548 | 0.9001 | 0.9081 | 0.9001 | 0.8990 | 0.9308 |
194
+ | 0.2103 | 17.92 | 6650 | 0.6355 | 0.8866 | 0.8983 | 0.8866 | 0.8839 | 0.9194 |
195
+ | 0.1962 | 18.06 | 6700 | 0.5878 | 0.9015 | 0.9120 | 0.9015 | 0.8983 | 0.9306 |
196
+ | 0.1962 | 18.19 | 6750 | 0.6067 | 0.8907 | 0.9015 | 0.8907 | 0.8890 | 0.9231 |
197
+ | 0.1962 | 18.33 | 6800 | 0.5797 | 0.8880 | 0.8989 | 0.8880 | 0.8863 | 0.9212 |
198
+ | 0.1962 | 18.46 | 6850 | 0.5842 | 0.8907 | 0.9020 | 0.8907 | 0.8894 | 0.9236 |
199
+ | 0.1962 | 18.6 | 6900 | 0.5838 | 0.8961 | 0.9078 | 0.8961 | 0.8947 | 0.9260 |
200
+ | 0.1962 | 18.73 | 6950 | 0.5655 | 0.8880 | 0.9021 | 0.8880 | 0.8876 | 0.9212 |
201
+ | 0.1962 | 18.87 | 7000 | 0.5601 | 0.8988 | 0.9088 | 0.8988 | 0.8977 | 0.9287 |
202
+ | 0.1881 | 19.0 | 7050 | 0.5815 | 0.8988 | 0.9077 | 0.8988 | 0.8972 | 0.9283 |
203
+ | 0.1881 | 19.14 | 7100 | 0.6380 | 0.8947 | 0.9054 | 0.8947 | 0.8932 | 0.9259 |
204
+ | 0.1881 | 19.27 | 7150 | 0.6770 | 0.8907 | 0.9004 | 0.8907 | 0.8892 | 0.9227 |
205
+ | 0.1881 | 19.41 | 7200 | 0.6608 | 0.8907 | 0.8997 | 0.8907 | 0.8890 | 0.9227 |
206
+ | 0.1881 | 19.54 | 7250 | 0.7075 | 0.8826 | 0.8974 | 0.8826 | 0.8815 | 0.9174 |
207
+ | 0.1881 | 19.68 | 7300 | 0.6649 | 0.8853 | 0.8992 | 0.8853 | 0.8827 | 0.9193 |
208
+ | 0.1881 | 19.81 | 7350 | 0.6430 | 0.8880 | 0.8983 | 0.8880 | 0.8868 | 0.9212 |
209
+
210
+
211
+ ### Framework versions
212
+
213
+ - Transformers 4.38.2
214
+ - Pytorch 2.3.0
215
+ - Datasets 2.19.1
216
+ - Tokenizers 0.15.1
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