BERT_BASE_TS_phonetic_wikitext_0.0
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.7259
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: 1e-05
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10000
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.0301 | 0.3019 | 2000 | 1.8848 |
1.9624 | 0.6039 | 4000 | 1.8266 |
1.9287 | 0.9058 | 6000 | 1.7743 |
1.9046 | 1.2077 | 8000 | 1.7480 |
1.8906 | 1.5097 | 10000 | 1.7608 |
1.87 | 1.8116 | 12000 | 1.7273 |
1.8541 | 2.1135 | 14000 | 1.7327 |
1.8471 | 2.4155 | 16000 | 1.7083 |
1.8402 | 2.7174 | 18000 | 1.7417 |
1.8292 | 3.0193 | 20000 | 1.7046 |
1.8243 | 3.3213 | 22000 | 1.7018 |
1.8155 | 3.6232 | 24000 | 1.7189 |
1.8152 | 3.9251 | 26000 | 1.6891 |
1.8077 | 4.2271 | 28000 | 1.6809 |
1.811 | 4.5290 | 30000 | 1.6852 |
1.8118 | 4.8309 | 32000 | 1.7259 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0
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Model tree for psktoure/BERT_BASE_TS_phonetic_wikitext_0.0
Base model
google-bert/bert-base-uncased