add model
Browse files- README.md +15 -13
- config.json +1 -1
- pytorch_model.bin +1 -1
- runs/Sep14_00-24-50_9d314cf99c57/1631579292.188806/events.out.tfevents.1631579292.9d314cf99c57.74.1 +3 -0
- runs/Sep14_00-24-50_9d314cf99c57/events.out.tfevents.1631579292.9d314cf99c57.74.0 +3 -0
- runs/Sep14_00-24-50_9d314cf99c57/events.out.tfevents.1631579789.9d314cf99c57.74.2 +3 -0
- training_args.bin +1 -1
README.md
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metrics:
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- name: Precision
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type: precision
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value: 0.
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- name: Recall
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type: recall
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value: 0.
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- name: F1
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type: f1
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value: 0.
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 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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- 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:
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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.
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### Framework versions
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- Transformers 4.10.
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- Pytorch 1.9.0+cu102
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- Datasets 1.
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- Tokenizers 0.10.3
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metrics:
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- name: Precision
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type: precision
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value: 0.9274238227146815
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- name: Recall
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type: recall
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value: 0.9363463474661595
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- name: F1
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type: f1
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value: 0.9318637274549098
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- name: Accuracy
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type: accuracy
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value: 0.9839865283492462
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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 [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the conll2003 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0614
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- Precision: 0.9274
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- Recall: 0.9363
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- F1: 0.9319
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- Accuracy: 0.9840
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## Model description
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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: 3
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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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| 0.2403 | 1.0 | 878 | 0.0701 | 0.9101 | 0.9202 | 0.9151 | 0.9805 |
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| 0.0508 | 2.0 | 1756 | 0.0600 | 0.9220 | 0.9350 | 0.9285 | 0.9833 |
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| 0.0301 | 3.0 | 2634 | 0.0614 | 0.9274 | 0.9363 | 0.9319 | 0.9840 |
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### Framework versions
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- Transformers 4.10.2
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- Pytorch 1.9.0+cu102
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- Datasets 1.12.0
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- Tokenizers 0.10.3
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config.json
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.10.
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"vocab_size": 30522
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}
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"sinusoidal_pos_embds": false,
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"tie_weights_": true,
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"torch_dtype": "float32",
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"transformers_version": "4.10.2",
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"vocab_size": 30522
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}
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pytorch_model.bin
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runs/Sep14_00-24-50_9d314cf99c57/1631579292.188806/events.out.tfevents.1631579292.9d314cf99c57.74.1
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training_args.bin
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