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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: eddieman78/onto-coref-mem-base
model-index:
- name: litbank-coref-mem-base
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# litbank-coref-mem-base
This model is a fine-tuned version of [eddieman78/onto-coref-mem-base](https://huggingface.co/eddieman78/onto-coref-mem-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0220
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log | 1.0 | 339 | 0.0255 |
| 0.0407 | 2.0 | 678 | 0.0221 |
| 0.0279 | 3.0 | 1017 | 0.0206 |
| 0.0279 | 4.0 | 1356 | 0.0197 |
| 0.0232 | 5.0 | 1695 | 0.0191 |
| 0.0212 | 6.0 | 2034 | 0.0189 |
| 0.0212 | 7.0 | 2373 | 0.0184 |
| 0.0193 | 8.0 | 2712 | 0.0184 |
| 0.0176 | 9.0 | 3051 | 0.0181 |
| 0.0176 | 10.0 | 3390 | 0.0187 |
| 0.0164 | 11.0 | 3729 | 0.0182 |
| 0.0155 | 12.0 | 4068 | 0.0183 |
| 0.0155 | 13.0 | 4407 | 0.0182 |
| 0.0143 | 14.0 | 4746 | 0.0185 |
| 0.0134 | 15.0 | 5085 | 0.0184 |
| 0.0134 | 16.0 | 5424 | 0.0187 |
| 0.0127 | 17.0 | 5763 | 0.0188 |
| 0.0121 | 18.0 | 6102 | 0.0186 |
| 0.0121 | 19.0 | 6441 | 0.0188 |
| 0.0118 | 20.0 | 6780 | 0.0192 |
| 0.0111 | 21.0 | 7119 | 0.0192 |
| 0.0111 | 22.0 | 7458 | 0.0191 |
| 0.0108 | 23.0 | 7797 | 0.0197 |
| 0.01 | 24.0 | 8136 | 0.0199 |
| 0.01 | 25.0 | 8475 | 0.0202 |
| 0.0098 | 26.0 | 8814 | 0.0200 |
| 0.0093 | 27.0 | 9153 | 0.0198 |
| 0.0093 | 28.0 | 9492 | 0.0200 |
| 0.0093 | 29.0 | 9831 | 0.0208 |
| 0.0089 | 30.0 | 10170 | 0.0203 |
| 0.0087 | 31.0 | 10509 | 0.0214 |
| 0.0087 | 32.0 | 10848 | 0.0203 |
| 0.0087 | 33.0 | 11187 | 0.0208 |
| 0.008 | 34.0 | 11526 | 0.0213 |
| 0.008 | 35.0 | 11865 | 0.0212 |
| 0.0079 | 36.0 | 12204 | 0.0215 |
| 0.0079 | 37.0 | 12543 | 0.0216 |
| 0.0079 | 38.0 | 12882 | 0.0217 |
| 0.0077 | 39.0 | 13221 | 0.0217 |
| 0.0075 | 40.0 | 13560 | 0.0219 |
| 0.0075 | 41.0 | 13899 | 0.0221 |
| 0.0074 | 42.0 | 14238 | 0.0218 |
| 0.0072 | 43.0 | 14577 | 0.0220 |
| 0.0072 | 44.0 | 14916 | 0.0220 |
| 0.0071 | 45.0 | 15255 | 0.0220 |
| 0.0072 | 46.0 | 15594 | 0.0220 |
| 0.0072 | 47.0 | 15933 | 0.0220 |
| 0.0071 | 48.0 | 16272 | 0.0220 |
| 0.0072 | 49.0 | 16611 | 0.0220 |
| 0.0072 | 50.0 | 16950 | 0.0220 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.2
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