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npi-sent-neg-lstm-1
CLMBR/npi-sent-neg-lstm-1
npi-sent-neg-lstm-1 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 18, 2024
- Updated
- Jan 23, 2024
- SHA
- e4f09ae4
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. -->
npi-sent-neg-lstm-1
This model is a fine-tuned version of on the None dataset. It achieves the following results on the evaluation set:
- Loss: 3.9724
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: 1
- 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 |
|---|---|---|---|
| 4.7981 | 0.03 | 76320 | 4.7641 |
| 4.5144 | 1.03 | 152640 | 4.4830 |
| 4.37 | 0.03 | 228960 | 4.3471 |
| 4.2871 | 1.03 | 305280 | 4.2640 |
| 4.2243 | 0.03 | 381600 | 4.2066 |
| 4.1794 | 0.03 | 457920 | 4.1658 |
| 4.142 | 1.03 | 534240 | 4.1345 |
| 4.1091 | 0.03 | 610560 | 4.1103 |
| 4.0804 | 1.03 | 686880 | 4.0904 |
| 4.0533 | 0.03 | 763200 | 4.0740 |
| 4.029 | 1.03 | 839520 | 4.0605 |
| 4.0156 | 0.03 | 915840 | 4.0497 |
| 3.9955 | 1.03 | 992160 | 4.0397 |
| 3.9746 | 0.03 | 1068480 | 4.0307 |
| 3.9655 | 1.03 | 1144800 | 4.0248 |
| 3.9539 | 0.03 | 1221120 | 4.0186 |
| 3.9435 | 1.03 | 1297440 | 4.0140 |
| 3.9357 | 0.03 | 1373760 | 4.0090 |
| 3.9227 | 1.03 | 1450080 | 4.0046 |
| 3.9239 | 0.03 | 1526400 | 4.0009 |
| 3.9158 | 1.03 | 1602720 | 3.9978 |
| 3.9149 | 0.03 | 1679040 | 3.9947 |
| 3.9098 | 1.03 | 1755360 | 3.9922 |
| 3.9045 | 0.03 | 1831680 | 3.9899 |
| 3.8979 | 1.03 | 1908000 | 3.9885 |
| 3.8895 | 0.03 | 1984320 | 3.9865 |
| 3.8816 | 1.03 | 2060640 | 3.9846 |
| 3.8781 | 0.03 | 2136960 | 3.9832 |
| 3.8719 | 1.03 | 2213280 | 3.9814 |
| 3.8604 | 0.03 | 2289600 | 3.9800 |
| 3.8581 | 1.03 | 2365920 | 3.9787 |
| 3.8556 | 0.03 | 2442240 | 3.9777 |
| 3.8512 | 1.03 | 2518560 | 3.9763 |
| 3.8498 | 0.03 | 2594880 | 3.9755 |
| 3.8439 | 1.03 | 2671200 | 3.9749 |
| 3.8483 | 0.03 | 2747520 | 3.9742 |
| 3.8483 | 1.03 | 2823840 | 3.9736 |
| 3.8515 | 0.03 | 2900160 | 3.9730 |
| 3.851 | 1.03 | 2976480 | 3.9726 |
| 3.8506 | 0.02 | 3052726 | 3.9724 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.12.0
- Tokenizers 0.13.3
- Library
- transformers
- Type
- rnn
- Created
- Jan 18, 2024
- Updated
- Jan 23, 2024