metadata
language:
- en
license: mit
tags:
- generated_from_trainer
datasets:
- glue
metrics:
- accuracy
- f1
model-index:
- name: camembert-base-mrpc
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: GLUE MRPC
type: glue
args: mrpc
metrics:
- type: accuracy
value: 0.8504901960784313
name: Accuracy
- type: f1
value: 0.8927943760984183
name: F1
- task:
type: natural-language-inference
name: Natural Language Inference
dataset:
name: glue
type: glue
config: mrpc
split: validation
metrics:
- type: accuracy
value: 0.8504901960784313
name: Accuracy
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNWJjOGZiMzBlNjhhNTZlMjEzNTE5MDM2OTJmYzZhZTE2YzE0MWM0ZmY2Zjk5ZTkxYWE0NTEyMDVlMDI5N2MwZiIsInZlcnNpb24iOjF9.dLsmgphn4jg1LbcOwDagIBRtQJ3spLTOcPxOpVnNqE-oU6ttKxW-Ypg7arQxOV-swVu4xpl3SDGaqEDE5sZnCw
- type: precision
value: 0.8758620689655172
name: Precision
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiM2ZiY2ZiODZmOTJkN2I4YzYxY2NmMDc1NzQyMmI0MTI0MDlmYzkzNDhjMTA4NmIzNzNjNjE4NmMwMjI1MDRjMyIsInZlcnNpb24iOjF9.94XqLpsB43QQqsnh5ykt_jZuKXOjSbtwFgEUscatZzJdwIt0WBHY7oNpoodbZbk0eUDzTIoZyNoN59glXmlEAg
- type: recall
value: 0.910394265232975
name: Recall
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOTY3MDljNGM4ZjYxZjc1YmYyZTkwNjc4MTRmOTFjZjYyZDdlY2EyZTc4OWE0NWQ3ODIxY2NmODIzY2IxMWY5YiIsInZlcnNpb24iOjF9.BGacWdlFR1hw98mwV6P1UPbBInb4Z8XIpRkqqZdeQPpH9RBBdGoaiKuKx7FJKGDgMLEaqwleER4n6FSC7KaQDg
- type: auc
value: 0.9029062821260871
name: AUC
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMDU0ZjdjZGNjNjAxZWM3NzNlYmM2NWFlZmYwZTY5ZDI2ZTY2ZTk0YTVhODc0NzcyMjNjOGFjOTY0YjYzMmU2ZCIsInZlcnNpb24iOjF9.jalnocWEmIaPkl1l-kHZm9I49WumqCay5T5C3_5RKhPZMCidPIRB14Y7a6klepf19-__EmP34QS3HxEl5iVMBA
- type: f1
value: 0.8927943760984183
name: F1
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiN2I1MGVmODRlYTNjZTJmYWRiYTA5YzEyODkxYjQ2ZGNlMTliODAwMzMwNGEzMWQ2ZGRhYmYwZjVjMTgwNGU2NCIsInZlcnNpb24iOjF9.QgvEjsEulus1kvcBkHqV3RrcigOSNcfCbkKa6JWPCRxIyzbiFpNCvkFubSHbVPe0SX2h9vjgjmECv-SapMLKDg
- type: loss
value: 0.42868512868881226
name: loss
verified: true
verifyToken: >-
eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMjIwMjNiYzI4NzgwZGI5MWU2NDgzYTQzNTYwNGUwMmZlNmViODhhYWIzZGE1ZWIxYzExMzRiOTU1YzFhNWQ0OSIsInZlcnNpb24iOjF9.NUgxlMh9Z0EyRqeKRr3BYYk9L02EdmJM-alLPPecPkML_ZdcbWHW-JOQN_vUTgYNda80dUBKRj_FmJ4kRF4yAQ
camembert-base-mrpc
This model is a fine-tuned version of camembert-base on the GLUE MRPC dataset. It achieves the following results on the evaluation set:
- Loss: 0.4286
- Accuracy: 0.8505
- F1: 0.8928
- Combined Score: 0.8716
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5.0
Training results
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu102
- Datasets 2.1.0
- Tokenizers 0.11.6