--- license: mit tags: - generated_from_trainer datasets: - emotion metrics: - f1 model-index: - name: minilm-finetuned-emotion results: - task: type: text-classification name: Text Classification dataset: name: emotion type: emotion args: default metrics: - type: f1 value: 0.9117582218338629 name: F1 - task: type: text-classification name: Text Classification dataset: name: emotion type: emotion config: default split: test metrics: - type: accuracy value: 0.9135 name: Accuracy verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGUyODMzMjBmZWE4M2Y3OTRkOThhYjY5MGNiNzc3YTVhMjhjYWU5Nzc3Y2I2ZmM3ZmY4MTg5Mjg5ZWQyNjRjMSIsInZlcnNpb24iOjF9.fg4k9vFS45061Sfds1QysUVXohn78EA67kFdR9dS3mD6YEivYvJJhtg-HxwB85tCK3HKG9kJ8fZDBZpl80VHBQ - type: f1 value: 0.8605041780075561 name: F1 Macro verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiYzU1MjAyYTNiYWQ3YmIzMjM1YWY0YTliNDA3NzkwZGM4NzIwMTI0OGE1MGFjNDZmZTgxMGMyYjE5Yjk0ZWI2OSIsInZlcnNpb24iOjF9.tvCoRtiOJZK-aj1NTguVTgalYv7dpr53HltxIaHSK8RYiOGTtTPWyoD2S6HNr6TcyG_xpiAGSvAX8aPB7BrPAA - type: f1 value: 0.9135 name: F1 Micro verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiOGZiZDczYzA3ZTlhYzhmY2U0MjU1NTQyNjUzMDQ4MzNjNDE5YmFjMzVlNDA3ZDE5ZGQ1ZDM4ODk2MDBhMGRkOSIsInZlcnNpb24iOjF9._jIY8LU8dEQtvxfWkFEZqwGCdnz2T7GFAOVIj2yonoQkRc49gUhjPuwVjW_0B4N420omnCc6HaNEgEdf9MvICw - type: f1 value: 0.9137710447678835 name: F1 Weighted verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTEzZTA2MWZlMTVkMWEwZTU5YzBhZjE5MmVjM2RhNGQ0NzFmNmQ0NTg1Njk5OGU3OWNmODhjNDZmMzdkNzk2MCIsInZlcnNpb24iOjF9.nuj-Ek1A_ol3VHdTMUfSr91PNQ_SA7XkIXplIRVg-f77DpUChzvxZPfGYo8Epvz8F5KNW7NKEZI-DWxhgftRDg - type: precision value: 0.8837842447434209 name: Precision Macro verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZTcxODM5NWY0Yjk4NjNhOWYyNjhhMWE2MGE2MjBjMmQxZjkxMmVlM2JiMTkxMTRmZTU5Zjk5YzM3NmZjOTJmNSIsInZlcnNpb24iOjF9.FSHEuPvH2dVPlmeXrTb5UbVNCuHzo_nOwMS644pPC12VhguiPPFoYX9VzNf7i_yG5bRK6rvo3gGu8kbQpm6qCg - type: precision value: 0.9135 name: Precision Micro verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiNTM5ZjVkYmMxYjQ4NWNkOTZhZjgwYzVjNDFjOTQxZGU5YTQ0YzVjNTJlMGQyOGIyYzgzN2MyODA3ZTRmNmMyZSIsInZlcnNpb24iOjF9.yo1fZWoORSRyrpuEwHqe2qEW_c50ljfMHN0QonCjP2dtjcVMj7vK8_AsT6jLNK2fts9zC2D_Mrx0pJKtxV8MDg - type: precision value: 0.9214108255847144 name: Precision Weighted verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZmFkZjllYTZkMzkxOTVjYmRkMjgzM2ZjYzZmMWI3YWQ0ZDliMWI2YTJiODdiZmQ0MTU0NjMzZWJlNjUyODYyNyIsInZlcnNpb24iOjF9.In5jOw4QujbpBv3RRnxwuyDE9TwvWqgqV5W-3zgB5vUUimjYCF7DGePyEYW1UGu1VZ8p7GvX2VYkR-d84y72Cg - type: recall value: 0.8615717630413814 name: Recall Macro verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZDkyNWNlMTA3MjEzNDBmYWIxYjg1MDJmNjdhNTA0YWUwMDg5NTAzNzE5ZmM3OTdkNDc5ZTQxYTRhYTE2NzAyOCIsInZlcnNpb24iOjF9.ilrr0PKUcVwUUT3ouhurmZpB3F_xv-5bZlNiYGtZbR0CrKUlp2nXWYvt9bda7V6WIY2VHirQ6n_n5Q9eZrN2AA - type: recall value: 0.9135 name: Recall Micro verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZWMyOGJkNmY5OWI5YTk3NDY4ZGU4OTNkYzRkMDM5YjBhYWM4OWYyNWIwMmUyNDBkZWI3OGFmMjM1ZDI4NjIwNyIsInZlcnNpb24iOjF9.gRhGm18KDj9G2iC097Y8qhnMFryrfuMZROGce-eQTkeeogA1jYMq-iYge5wXkDyNFANe7K7Tgl07uLOFYDXoCQ - type: recall value: 0.9135 name: Recall Weighted verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiMGQ1MzgxMGIzYmI5Njc2N2VjYTVlNWIzYmQ1MmRmYTc4YmI0NGM0MWZmOGZkZTkyMDM3OWJhMDNiZjE2ZDY2ZCIsInZlcnNpb24iOjF9.CeoluasKQgxZ2xj6DLE3XboZTNmVl1-ArG_f5Chw-eM8QhcyrIhTfCbzqX5bCop3OAccUQRXzAOjao1DAMblDQ - type: loss value: 0.3407318592071533 name: loss verified: true verifyToken: eyJhbGciOiJFZERTQSIsInR5cCI6IkpXVCJ9.eyJoYXNoIjoiZGU2ZTVhZjFlZDU5NmM0NWE4ZWEzMjZjY2QwOWMxZWVkYmMzZjU3NmY0N2MwOWM4OTFkODY0MTE4NzliNGZhMiIsInZlcnNpb24iOjF9.A2VEIKr0YfKr6IJfMbtCLTKrY724QxFJ-bx4ZAJS4lG087Zl2ngjEZhsHEArvCWygaMt9nS9Eu07qVs3DeAADA --- # minilm-finetuned-emotion This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co/microsoft/MiniLM-L12-H384-uncased) on the emotion dataset. It achieves the following results on the evaluation set: - Loss: 0.3891 - F1: 0.9118 ## 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: 64 - eval_batch_size: 64 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | F1 | |:-------------:|:-----:|:----:|:---------------:|:------:| | 1.3957 | 1.0 | 250 | 1.0134 | 0.6088 | | 0.8715 | 2.0 | 500 | 0.6892 | 0.8493 | | 0.6085 | 3.0 | 750 | 0.4943 | 0.8920 | | 0.4626 | 4.0 | 1000 | 0.4096 | 0.9078 | | 0.3961 | 5.0 | 1250 | 0.3891 | 0.9118 | ### Framework versions - Transformers 4.12.3 - Pytorch 1.6.0 - Datasets 1.15.1 - Tokenizers 0.10.3