metadata
license: apache-2.0
base_model: mnaylor/mega-base-wikitext
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: mega-base-multiple-choice-fp16-v2
results: []
mega-base-multiple-choice-fp16-v2
This model is a fine-tuned version of mnaylor/mega-base-wikitext on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6932
- Accuracy: 0.5010
- Precision: 0.5010
- Recall: 0.4964
- F1: 0.4987
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: 0.005
- train_batch_size: 1024
- eval_batch_size: 1024
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 24000
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 34 | 0.6931 | 0.5021 | 0.5021 | 0.5076 | 0.5048 |
| No log | 2.0 | 68 | 0.6932 | 0.5050 | 0.5049 | 0.5102 | 0.5076 |
| No log | 3.0 | 102 | 0.6932 | 0.5010 | 0.5010 | 0.4964 | 0.4987 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0