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--- |
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language: |
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- en |
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license: mit |
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tags: |
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- generated_from_trainer |
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datasets: |
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- glue |
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metrics: |
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- accuracy |
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model-index: |
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- name: roberta-base-rte |
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results: |
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- task: |
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type: text-classification |
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name: Text Classification |
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dataset: |
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name: GLUE RTE |
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type: glue |
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args: rte |
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metrics: |
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- type: accuracy |
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value: 0.7978339350180506 |
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name: Accuracy |
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- task: |
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type: natural-language-inference |
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name: Natural Language Inference |
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dataset: |
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name: glue |
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type: glue |
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config: rte |
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split: validation |
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metrics: |
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- type: accuracy |
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value: 0.7906137184115524 |
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name: Accuracy |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMWVhOWZkNGYyMWRmNzdmZTM5MTVmNzFhNjVlMzA1NWU4YjJjODk5ZjM4MTY1Yjg0MTc0MmRmZTNkMzIwZDAzNyIsInZlcnNpb24iOjF9.nFZpFXDSLEIcO-_Z43_5b08GIVQiU9hFUEZpTftW3h6_zqIYZSuM7jOIuDYS3YYWMz42NoH_kosEpJg7TK15Bg |
|
- type: precision |
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value: 0.7552447552447552 |
|
name: Precision |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNDYxZTkzZjk1NDU0MjhmNzYxM2IzNzJjNjE1Y2UxYTQ0MTJmNjJlMmUzNGY3MDdiMDAyZjQ2MmE4ODExYjYxNiIsInZlcnNpb24iOjF9.98rxE2rgU5ECIv4MGzMnaPRRYg3kGLsG4pZbMuYeAFEfXqBU1K0i_G-_cU7oxIqGypNmMhYVhVxZfC7wS_saAw |
|
- type: recall |
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value: 0.8244274809160306 |
|
name: Recall |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTNhNDZiZjMzOWM0ZGJkODMzM2VmOGYxMTYyZDNjYTgwN2NiMDFlOGI4NzM5NjQ5ODc4MWM2YmM5MTZjMWFiOCIsInZlcnNpb24iOjF9.C9aEgIz392h-zFSd98CSmzQ7Y6N0Xq3VmGIMEq9aP3dQPPrtUfl9Ms_QMSgSyWMPDYHup3SAGAP0JmkiVeOoBg |
|
- type: auc |
|
value: 0.8564258078008994 |
|
name: AUC |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWVlNGVhOTRkNjUxMGMwZmE0YzBjZDQ0YzQ0ODRmYTc0YjI0MDQ2NTNkOWQ2YjU3MmI5NzI4ZWIwMzBlNTQ1NyIsInZlcnNpb24iOjF9.hSyJjOktSt3AItNnVtgWO9jgHwtNbhv4_KrWEV1r_ywopvbpNmSG4yzaI9PZ_bQQ-4ZSmFM8zUYxCl656TWoDQ |
|
- type: f1 |
|
value: 0.7883211678832117 |
|
name: F1 |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNGI4Mzk1MTkyZGJkZjQ1MWZkZDIyZTA3OTU0YmZhNjI4NGUxMjk4ZGZhNjZkN2JmZWRmZGU3OWM5Zjc0ODg4NyIsInZlcnNpb24iOjF9.gkQh5Y4dm8NimTtI0i-gHAYTxFRNlOtdgz-NJW8EvNKeFNWYXqa495Q-KEnSBRv88RKiNQXBp-3fyttjhX2HCw |
|
- type: loss |
|
value: 0.5560466051101685 |
|
name: loss |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjczNTgxODRlN2Q4NmUyOTdjNzE0ZTZkOWVjZDgzNTdhODAyNGVkM2M1M2I4MGM2ZWMyMDE0ODdhMzQ0N2E1NCIsInZlcnNpb24iOjF9.TfXjqAGtiIQ62HzMkEQmKMMcL9a9bvfBTJARVmTPlIdOOxxF-xuVLXSyFqq2ajhDJXmUEETXBcFzSon_zbHTCQ |
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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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# roberta-base-rte |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the GLUE RTE dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5446 |
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- Accuracy: 0.7978 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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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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- lr_scheduler_warmup_ratio: 0.06 |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 156 | 0.7023 | 0.4729 | |
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| No log | 2.0 | 312 | 0.6356 | 0.6895 | |
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| No log | 3.0 | 468 | 0.5177 | 0.7617 | |
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| 0.6131 | 4.0 | 624 | 0.6238 | 0.7473 | |
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| 0.6131 | 5.0 | 780 | 0.5446 | 0.7978 | |
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| 0.6131 | 6.0 | 936 | 0.9697 | 0.7545 | |
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| 0.2528 | 7.0 | 1092 | 1.1004 | 0.7690 | |
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| 0.2528 | 8.0 | 1248 | 1.1937 | 0.7726 | |
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| 0.2528 | 9.0 | 1404 | 1.3313 | 0.7726 | |
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| 0.1073 | 10.0 | 1560 | 1.3534 | 0.7726 | |
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### Framework versions |
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- Transformers 4.20.0.dev0 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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