metadata
license: apache-2.0
base_model: bert-large-cased
tags:
- generated_from_trainer
metrics:
- f1
- precision
- recall
- accuracy
model-index:
- name: sequence-ranker-llm-last-layer
results: []
sequence-ranker-llm-last-layer
This model is a fine-tuned version of bert-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7482
- F1: 0.0
- Precision: 0.0
- Recall: 0.0
- Accuracy: 0.8266
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Precision | Recall | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.6058 | 1.0 | 284 | 0.7464 | 0.0 | 0.0 | 0.0 | 0.8266 |
| 0.5918 | 2.0 | 568 | 0.7482 | 0.0 | 0.0 | 0.0 | 0.8266 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2