mt5-small-gigatrue-layercut-D5
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4092
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: 0.0003
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 3.6665 | 0.1015 | 3000 | 2.5503 |
| 3.1237 | 0.2030 | 6000 | 2.4814 |
| 3.0657 | 0.3044 | 9000 | 2.4631 |
| 3.0389 | 0.4059 | 12000 | 2.4435 |
| 3.0188 | 0.5074 | 15000 | 2.4455 |
| 3.0112 | 0.6089 | 18000 | 2.4229 |
| 3.0059 | 0.7104 | 21000 | 2.4302 |
| 3.0001 | 0.8119 | 24000 | 2.4221 |
| 2.994 | 0.9133 | 27000 | 2.4214 |
| 2.9932 | 1.0148 | 30000 | 2.4205 |
| 2.991 | 1.1163 | 33000 | 2.4148 |
| 2.9857 | 1.2178 | 36000 | 2.4131 |
| 2.985 | 1.3193 | 39000 | 2.4148 |
| 2.9831 | 1.4207 | 42000 | 2.4104 |
| 2.9842 | 1.5222 | 45000 | 2.4128 |
| 2.9785 | 1.6237 | 48000 | 2.4131 |
| 2.9817 | 1.7252 | 51000 | 2.4099 |
| 2.9754 | 1.8267 | 54000 | 2.4114 |
| 2.977 | 1.9282 | 57000 | 2.4088 |
| 2.9784 | 2.0296 | 60000 | 2.4082 |
| 2.9792 | 2.1311 | 63000 | 2.4095 |
| 2.9768 | 2.2326 | 66000 | 2.4102 |
| 2.9773 | 2.3341 | 69000 | 2.4096 |
| 2.9764 | 2.4356 | 72000 | 2.4085 |
| 2.9771 | 2.5370 | 75000 | 2.4076 |
| 2.9795 | 2.6385 | 78000 | 2.4085 |
| 2.9768 | 2.7400 | 81000 | 2.4088 |
| 2.9762 | 2.8415 | 84000 | 2.4093 |
| 2.9776 | 2.9430 | 87000 | 2.4092 |
Framework versions
- Transformers 4.45.2
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.20.3