my_awesome_wnut_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on the wnut_17 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2751
- eval_precision: 0.5915
- eval_recall: 0.2456
- eval_f1: 0.3471
- eval_accuracy: 0.9388
- eval_runtime: 3.0704
- eval_samples_per_second: 419.16
- eval_steps_per_second: 26.381
- epoch: 1.0
- step: 213
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: 16
- seed: 42
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Framework versions
- Transformers 4.36.1
- Pytorch 2.0.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Model tree for mandasrinu/my_awesome_wnut_model
Base model
distilbert/distilbert-base-uncased