Capreolus_bert-base-msmarco-finetuned-lora-tweet_eval_emotion
This model is a fine-tuned version of Capreolus/bert-base-msmarco on the tweet_eval dataset. It achieves the following results on the evaluation set:
- accuracy: 0.7005
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: 0.0004
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
accuracy | train_loss | epoch |
---|---|---|
0.4278 | None | 0 |
0.5187 | 1.2591 | 0 |
0.6765 | 1.0317 | 1 |
0.7059 | 0.8817 | 2 |
0.7005 | 0.8248 | 3 |
Framework versions
- PEFT 0.8.2
- Transformers 4.37.2
- Pytorch 2.2.0
- Datasets 2.16.1
- Tokenizers 0.15.2
- Downloads last month
- 6
Inference API (serverless) does not yet support peft models for this pipeline type.
Model tree for TransferGraph/Capreolus_bert-base-msmarco-finetuned-lora-tweet_eval_emotion
Base model
Capreolus/bert-base-msmarcoDataset used to train TransferGraph/Capreolus_bert-base-msmarco-finetuned-lora-tweet_eval_emotion
Evaluation results
- accuracy on tweet_evalvalidation set self-reported0.701