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balanced-augmented-ft-roberta-gest-pred-seqeval-partialmatch

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+ ---
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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-mlroberta-gest-pred-seqeval-partialmatch
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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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+ # balanced-augmented-mlroberta-gest-pred-seqeval-partialmatch
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+
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+ This model is a fine-tuned version of [xlm-roberta-large-finetuned-conll03-english](https://huggingface.co/xlm-roberta-large-finetuned-conll03-english) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1691
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+ - Precision: 0.8311
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+ - Recall: 0.8196
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+ - F1: 0.8166
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+ - Accuracy: 0.8015
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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: 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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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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+ | 3.1888 | 1.0 | 32 | 2.4935 | 0.2783 | 0.1689 | 0.1470 | 0.3131 |
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+ | 2.25 | 2.0 | 64 | 1.6646 | 0.6169 | 0.5430 | 0.5416 | 0.5888 |
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+ | 1.4955 | 3.0 | 96 | 1.2759 | 0.7516 | 0.6600 | 0.6688 | 0.6586 |
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+ | 0.9512 | 4.0 | 128 | 1.0307 | 0.8052 | 0.7394 | 0.7513 | 0.7147 |
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+ | 0.6053 | 5.0 | 160 | 0.9993 | 0.7975 | 0.7757 | 0.7724 | 0.7398 |
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+ | 0.4064 | 6.0 | 192 | 0.9347 | 0.8335 | 0.7939 | 0.7988 | 0.7732 |
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+ | 0.2802 | 7.0 | 224 | 0.9249 | 0.8285 | 0.7970 | 0.8013 | 0.7818 |
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+ | 0.2062 | 8.0 | 256 | 0.9051 | 0.8395 | 0.8114 | 0.8189 | 0.7987 |
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+ | 0.1372 | 9.0 | 288 | 0.9771 | 0.8447 | 0.7922 | 0.8079 | 0.7910 |
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+ | 0.1 | 10.0 | 320 | 1.0232 | 0.8246 | 0.8086 | 0.8042 | 0.7974 |
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+ | 0.0815 | 11.0 | 352 | 1.0103 | 0.8391 | 0.8173 | 0.8209 | 0.8024 |
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+ | 0.0586 | 12.0 | 384 | 1.0424 | 0.8366 | 0.7980 | 0.8085 | 0.7932 |
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+ | 0.0534 | 13.0 | 416 | 1.1246 | 0.8318 | 0.8070 | 0.8126 | 0.7969 |
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+ | 0.0412 | 14.0 | 448 | 1.0816 | 0.8338 | 0.8186 | 0.8167 | 0.8028 |
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+ | 0.0346 | 15.0 | 480 | 1.1178 | 0.8277 | 0.8222 | 0.8182 | 0.8037 |
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+ | 0.0312 | 16.0 | 512 | 1.1570 | 0.8387 | 0.8237 | 0.8219 | 0.8037 |
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+ | 0.0268 | 17.0 | 544 | 1.1548 | 0.8375 | 0.8279 | 0.8240 | 0.8028 |
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+ | 0.0221 | 18.0 | 576 | 1.1514 | 0.8316 | 0.8149 | 0.8169 | 0.8005 |
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+ | 0.0215 | 19.0 | 608 | 1.1698 | 0.8351 | 0.8221 | 0.8204 | 0.8037 |
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+ | 0.0213 | 20.0 | 640 | 1.1691 | 0.8311 | 0.8196 | 0.8166 | 0.8015 |
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+
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+
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+ ### Framework versions
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+
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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