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rel-cl-lstm-2
CLMBR/rel-cl-lstm-2
rel-cl-lstm-2 is a machine learning model from CLMBR. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- Model type
- rnn
- Access
- Public
- Created
- Jan 26, 2024
- Updated
- Feb 2, 2024
- SHA
- 0f42bada
Model card
From the Hugging Face model README
<!-- 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. -->
rel-cl2-lstm-2
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.9808
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 3052726
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 4.8075 | 0.03 | 76320 | 4.7715 |
| 4.5233 | 1.03 | 152640 | 4.4891 |
| 4.3831 | 0.03 | 228960 | 4.3540 |
| 4.2934 | 1.03 | 305280 | 4.2712 |
| 4.2326 | 0.03 | 381600 | 4.2147 |
| 4.1845 | 1.03 | 457920 | 4.1724 |
| 4.143 | 0.03 | 534240 | 4.1408 |
| 4.1105 | 1.03 | 610560 | 4.1176 |
| 4.081 | 0.03 | 686880 | 4.0976 |
| 4.0578 | 1.03 | 763200 | 4.0816 |
| 4.0362 | 0.03 | 839520 | 4.0684 |
| 4.0191 | 1.03 | 915840 | 4.0569 |
| 4.0014 | 0.03 | 992160 | 4.0468 |
| 3.9866 | 1.03 | 1068480 | 4.0398 |
| 3.9777 | 0.03 | 1144800 | 4.0328 |
| 3.9631 | 1.03 | 1221120 | 4.0265 |
| 3.9475 | 0.03 | 1297440 | 4.0213 |
| 3.9387 | 1.03 | 1373760 | 4.0167 |
| 3.9312 | 0.03 | 1450080 | 4.0121 |
| 3.9247 | 1.03 | 1526400 | 4.0087 |
| 3.9214 | 2.03 | 1602720 | 4.0049 |
| 3.9176 | 0.03 | 1679040 | 4.0025 |
| 3.909 | 0.03 | 1755360 | 3.9991 |
| 3.9035 | 1.03 | 1831680 | 3.9967 |
| 3.8969 | 0.03 | 1908000 | 3.9954 |
| 3.8922 | 1.03 | 1984320 | 3.9938 |
| 3.884 | 0.03 | 2060640 | 3.9921 |
| 3.8804 | 1.03 | 2136960 | 3.9902 |
| 3.8743 | 0.03 | 2213280 | 3.9888 |
| 3.8693 | 1.03 | 2289600 | 3.9874 |
| 3.869 | 0.03 | 2365920 | 3.9863 |
| 3.8625 | 0.03 | 2442240 | 3.9854 |
| 3.8571 | 1.03 | 2518560 | 3.9844 |
| 3.8528 | 0.03 | 2594880 | 3.9836 |
| 3.8525 | 0.03 | 2671200 | 3.9831 |
| 3.8521 | 1.03 | 2747520 | 3.9822 |
| 3.8535 | 0.03 | 2823840 | 3.9818 |
| 3.8537 | 1.03 | 2900160 | 3.9814 |
| 3.8522 | 0.03 | 2976480 | 3.9810 |
| 3.8514 | 1.02 | 3052726 | 3.9808 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- rnn
- Created
- Jan 26, 2024
- Updated
- Feb 2, 2024