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--- |
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license: apache-2.0 |
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widget: |
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- text: I'm fine. Who is this? |
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- text: You can't take anything seriously. |
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- text: In the end he's going to croak, isn't he? |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: balanced-augmented-bert-gest-pred-seqeval-partialmatch |
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results: [] |
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pipeline_tag: token-classification |
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datasets: |
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- Jsevisal/balanced_augmented_dataset |
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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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# balanced-augmented-bert-gest-pred-seqeval-partialmatch |
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This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8382 |
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- Precision: 0.8478 |
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- Recall: 0.8224 |
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- F1: 0.8293 |
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- Accuracy: 0.8118 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 3.3729 | 1.0 | 32 | 2.8438 | 0.0806 | 0.0549 | 0.0294 | 0.1986 | |
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| 2.7169 | 2.0 | 64 | 2.2356 | 0.4355 | 0.2940 | 0.2982 | 0.4307 | |
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| 2.0107 | 3.0 | 96 | 1.7202 | 0.6950 | 0.5187 | 0.5245 | 0.5698 | |
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| 1.4085 | 4.0 | 128 | 1.3703 | 0.7994 | 0.6487 | 0.6499 | 0.6582 | |
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| 0.9974 | 5.0 | 160 | 1.1172 | 0.8205 | 0.7349 | 0.7514 | 0.7156 | |
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| 0.6996 | 6.0 | 192 | 1.0020 | 0.8220 | 0.7550 | 0.7684 | 0.7451 | |
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| 0.492 | 7.0 | 224 | 0.9132 | 0.8203 | 0.7626 | 0.7722 | 0.7549 | |
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| 0.3593 | 8.0 | 256 | 0.8785 | 0.8475 | 0.8042 | 0.8135 | 0.7921 | |
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| 0.2618 | 9.0 | 288 | 0.8383 | 0.8395 | 0.8135 | 0.8199 | 0.7999 | |
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| 0.1928 | 10.0 | 320 | 0.8410 | 0.8433 | 0.8165 | 0.8240 | 0.8014 | |
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| 0.1541 | 11.0 | 352 | 0.8382 | 0.8478 | 0.8224 | 0.8293 | 0.8118 | |
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| 0.1216 | 12.0 | 384 | 0.8667 | 0.8259 | 0.8253 | 0.8210 | 0.8046 | |
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| 0.096 | 13.0 | 416 | 0.8726 | 0.8471 | 0.8253 | 0.8301 | 0.8133 | |
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| 0.0767 | 14.0 | 448 | 0.8826 | 0.8475 | 0.8307 | 0.8330 | 0.8102 | |
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| 0.0696 | 15.0 | 480 | 0.8964 | 0.8411 | 0.8285 | 0.8303 | 0.8149 | |
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| 0.057 | 16.0 | 512 | 0.9194 | 0.8365 | 0.8292 | 0.8289 | 0.8097 | |
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| 0.0514 | 17.0 | 544 | 0.9085 | 0.8502 | 0.8277 | 0.8326 | 0.8118 | |
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| 0.0468 | 18.0 | 576 | 0.9261 | 0.8345 | 0.8250 | 0.8243 | 0.8092 | |
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| 0.0437 | 19.0 | 608 | 0.9279 | 0.8394 | 0.8258 | 0.8270 | 0.8118 | |
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| 0.0414 | 20.0 | 640 | 0.9263 | 0.8443 | 0.8275 | 0.8298 | 0.8139 | |
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### Framework versions |
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- Transformers 4.27.3 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
