litbank-coref-mem-large-triple-chunk
This model is a fine-tuned version of eddieman78/litbank-coref-mem-large-triple on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0069
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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.0053 | 0.2896 | 500 | 0.0080 |
0.0058 | 0.5792 | 1000 | 0.0080 |
0.0052 | 0.8688 | 1500 | 0.0074 |
0.0049 | 1.1581 | 2000 | 0.0074 |
0.0044 | 1.4477 | 2500 | 0.0074 |
0.0043 | 1.7373 | 3000 | 0.0070 |
0.004 | 2.0266 | 3500 | 0.0068 |
0.0038 | 2.3162 | 4000 | 0.0071 |
0.0034 | 2.6058 | 4500 | 0.0070 |
0.0037 | 2.8955 | 5000 | 0.0069 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
- Downloads last month
- 5
Inference Providers
NEW
This model isn't deployed by any Inference Provider.
๐
Ask for provider support
Model tree for eddieman78/litbank-coref-mem-large-triple-chunk
Base model
google/flan-t5-large