add model
Browse files- README.md +17 -12
- pytorch_model.bin +1 -1
- runs/Aug20_12-20-27_ip-172-31-23-147/1629462041.0933988/events.out.tfevents.1629462041.ip-172-31-23-147.8390.1 +3 -0
- runs/Aug20_12-20-27_ip-172-31-23-147/events.out.tfevents.1629462041.ip-172-31-23-147.8390.0 +3 -0
- runs/Aug20_12-20-27_ip-172-31-23-147/events.out.tfevents.1629471031.ip-172-31-23-147.8390.2 +3 -0
- training_args.bin +1 -1
README.md
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metric:
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name: Accuracy
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type: accuracy
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value: 0.
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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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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the nerd dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Precision: 0.
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- Recall: 0.
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- F1: 0.
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- Accuracy: 0.
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## Model description
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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_ratio: 0.1
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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### Framework versions
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metric:
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name: Accuracy
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type: accuracy
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value: 0.9058961278375514
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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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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the nerd dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5332
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- Precision: 0.6337
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- Recall: 0.6731
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- F1: 0.6528
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- Accuracy: 0.9059
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## Model description
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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_ratio: 0.1
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- num_epochs: 10
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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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| 0.6337 | 1.0 | 8235 | 0.3391 | 0.5974 | 0.6567 | 0.6256 | 0.9010 |
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| 0.3086 | 2.0 | 16470 | 0.3188 | 0.6276 | 0.6607 | 0.6437 | 0.9061 |
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| 0.2394 | 3.0 | 24705 | 0.3304 | 0.6284 | 0.6740 | 0.6504 | 0.9064 |
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| 0.1841 | 4.0 | 32940 | 0.3451 | 0.6286 | 0.6749 | 0.6509 | 0.9065 |
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| 0.1392 | 5.0 | 41175 | 0.3837 | 0.6251 | 0.6745 | 0.6489 | 0.9056 |
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| 0.1056 | 6.0 | 49410 | 0.4185 | 0.6307 | 0.6751 | 0.6521 | 0.9057 |
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| 0.0812 | 7.0 | 57645 | 0.4615 | 0.6288 | 0.6774 | 0.6522 | 0.9052 |
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| 0.0629 | 8.0 | 65880 | 0.4933 | 0.6332 | 0.6755 | 0.6537 | 0.9065 |
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| 0.0492 | 9.0 | 74115 | 0.5266 | 0.6360 | 0.6752 | 0.6550 | 0.9067 |
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| 0.0401 | 10.0 | 82350 | 0.5452 | 0.6340 | 0.6760 | 0.6543 | 0.9065 |
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### Framework versions
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pytorch_model.bin
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runs/Aug20_12-20-27_ip-172-31-23-147/1629462041.0933988/events.out.tfevents.1629462041.ip-172-31-23-147.8390.1
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training_args.bin
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