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--- |
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language: |
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- en |
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license: apache-2.0 |
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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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base_model: bert-base-uncased |
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model-index: |
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- name: bert-base-uncased-mnli |
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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 MNLI |
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type: glue |
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args: mnli |
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metrics: |
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- type: accuracy |
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value: 0.8500813669650122 |
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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: mnli_matched |
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split: validation |
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metrics: |
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- type: accuracy |
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value: 0.8467651553744269 |
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name: Accuracy |
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verified: true |
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2MwZjZhM2RlMmU5Mjg5NzE0MTA3ODdjZGQwN2U5ZWNhYWUzMmRjMmVhMGEyMjQ3ZGMwOGRjNzkzM2VlNmUyOCIsInZlcnNpb24iOjF9.C6QBegyKVg-5xN06res-t3KxhUbC3kloOy_zf8Lxv981N2aNtmzpVPmiUimrESQj2j9h8PRhH3_shVd_iCpfCA |
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- type: precision |
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value: 0.8460148987014974 |
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name: Precision Macro |
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verified: true |
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWViM2QzYjgxZWFkMzlhMzA4ZjdiYzJjZTRhMDQwMjYwZmU3ZmQ5ZmU5YjgzY2FkOWNhMThhODczNjhiMWRiMyIsInZlcnNpb24iOjF9.yLUl2HVaLNjaQImJELdCZjGIqFoBjoCLMh4iijrlneVn87_fJxaieaES-lf6za141LSPSnHmp1H6SKo1L7GGCQ |
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- type: precision |
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value: 0.8467651553744269 |
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name: Precision Micro |
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verified: true |
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGIzMjJlMjIwNzA4YzAxYzQ5NGIxZjM0MWE2OWFlYTlmOTU5NzNjZTg0MTJiOTQ2N2U4NmE0NDFmNTc1MGQ5ZCIsInZlcnNpb24iOjF9.u-6lo01PvyYYLnVSc11mzEzga-p6b3gKxWLi_6ziAFZH_3HLZIqrdBoedqhkuRau5u6DcdUlGlWvs0k_7gxCBg |
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- type: precision |
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value: 0.8475656756385261 |
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name: Precision Weighted |
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verified: true |
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verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiY2FlZmE0MTMwNjRlN2MwZjZiMWY1OWE2OTM5MTc3N2Q2ZTVkMzBiYWUyMjU5YThlYjE1MGJkN2ViZTM3ODBhOCIsInZlcnNpb24iOjF9.0u0DToJ9Y_xstI5UB2yXydcHWPasql0z60zLONiRVWEjR6dbs2JzAHmRUrN3IO1QDRz5ssH0w979VRa-lyk3AA |
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- type: recall |
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value: 0.8463172075485045 |
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name: Recall Macro |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNzQ3MjA4MDI1YWZhYTg0NDliYjQ3NGQ5Y2I2NGI1NDNmNTQ3NjdkMmMxYWQ0NDExMzdhNzdmZWFmZTkyNGM5YiIsInZlcnNpb24iOjF9.veXK2iXkDSCDqM3_y3PyGwbZWsQRO_tvNRdmQB3vbvK1Bv4BYYL8WKUfIXm2Apr6IPRA0zeJNvfWIGnigX37Dg |
|
- type: recall |
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value: 0.8467651553744269 |
|
name: Recall Micro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDdlMzcwMzEyNWYxZGFhY2JkNzZmZWQ5NzU4ODQ2MjU3ODMzZGRmZmNlYTM2YTBkNTI4MjAzM2FkOWUxNDBlZSIsInZlcnNpb24iOjF9.rRyz3xQyJ4plzLAc7bJhSbTWdJB7ioX4qhaX6k0e52JL5RdBfwmMJc9lVPUhE70__10Hk_MdzLor5sFF1yaFAA |
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- type: recall |
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value: 0.8467651553744269 |
|
name: Recall Weighted |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTc2YzUwMWZjNGYyMjczNzk1YWJkZjkxMDI5NGRjMzdlMTU3YzZlZDQxNmI2YWE3MTQ3ZDVkMDAwY2NlNTA2NSIsInZlcnNpb24iOjF9.j4Kdqqo9LQxsb0A1TEd5K2U7j0qXrv50pbIc9DVdhoIrfIyFiSHuhPHIPZLubr-w0gVjn6aYl-kcM9EiGOSgCg |
|
- type: f1 |
|
value: 0.8459654597797398 |
|
name: F1 Macro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZjcxOWM1YjBiNDVlODZlMjUyZTMwNDUzOTM2MmM4MGNiN2QwOGY1MTE2YjhkZDJjNTlhM2JhMzI4MTcwZjMyYyIsInZlcnNpb24iOjF9.T7zjSHGRWPNMYIiEWGRQTeqY9LHMm0j-3RE3wmYJ5je--eoMhBa7AvRefmSQwZgJtmxwITGGpvXz-0qdfel3Ag |
|
- type: f1 |
|
value: 0.8467651553744269 |
|
name: F1 Micro |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzIzMjFlYzZmMmEyMDRlNDY5ZmYxOGMxZWM2ZjFjYmZlMTRlOTFiMjg3MWJmNmFjMzdkYTM2ODJlOGEwZWY1MSIsInZlcnNpb24iOjF9.1ZvHppu3JfoorjOpQooRVUFlsR1lLLoW_NoswdSsIUwyArbIDg6KRZLwxf-G40efl7hbdXZbr7Ey1WsyTdc0Dw |
|
- type: f1 |
|
value: 0.8469586362613581 |
|
name: F1 Weighted |
|
verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDM0MTlhYjZlNzBjNjIwNTQyMWIzN2VlNDU5ZmE5YWRlNGYyMGJmZTA4YzFjMGZmMmJlYTNiMzc0YjVhZjQ1NSIsInZlcnNpb24iOjF9.Na8fUEOkFTbctyzR7oSKJNTn2DCwHs-kEXUOBhz9_nxedczUDKiB1xOR372db9b3ot8ttlmceaNgBOnPIiBCBw |
|
- type: loss |
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value: 0.42515239119529724 |
|
name: loss |
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verified: true |
|
verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDg5NWViMWNmYjczN2ZmMjIzODg2ZGYxZmU2ZjdjM2M2MDZjYTI0ZDc4OTUwZDk3YzBiZmFlMjI4ZmQ4Zjg0YSIsInZlcnNpb24iOjF9.4g708h4xeFXdR0vYBgU70gr-I-rLns2RrPWUg4hEQTO4RzQ1fCe-54gH5kH3DTRwLJU4qJYL4SQNZOE-62ahDg |
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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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# bert-base-uncased-mnli |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on the GLUE MNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4056 |
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- Accuracy: 0.8501 |
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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: 32 |
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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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- num_epochs: 3.0 |
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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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| 0.4526 | 1.0 | 12272 | 0.4244 | 0.8388 | |
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| 0.3344 | 2.0 | 24544 | 0.4252 | 0.8469 | |
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| 0.2307 | 3.0 | 36816 | 0.4974 | 0.8445 | |
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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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