Text Classification
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distilbert
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Eval Results (legacy)
text-embeddings-inference
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Hartunka/bert_base_rand_20_v1_cola")
model = AutoModelForSequenceClassification.from_pretrained("Hartunka/bert_base_rand_20_v1_cola")Quick Links
bert_base_rand_20_v1_cola
This model is a fine-tuned version of Hartunka/bert_base_rand_20_v1 on the GLUE COLA dataset. It achieves the following results on the evaluation set:
- Loss: 0.6162
- Matthews Correlation: 0.0293
- Accuracy: 0.6836
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: 256
- eval_batch_size: 256
- seed: 10
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation | Accuracy |
|---|---|---|---|---|---|
| 0.6148 | 1.0 | 34 | 0.6175 | 0.0464 | 0.6922 |
| 0.5918 | 2.0 | 68 | 0.6162 | 0.0293 | 0.6836 |
| 0.545 | 3.0 | 102 | 0.6346 | 0.1012 | 0.6702 |
| 0.4906 | 4.0 | 136 | 0.7282 | 0.0907 | 0.6654 |
| 0.4302 | 5.0 | 170 | 0.6911 | 0.0949 | 0.6548 |
| 0.3838 | 6.0 | 204 | 0.8097 | 0.0868 | 0.6261 |
| 0.3359 | 7.0 | 238 | 0.8488 | 0.1074 | 0.6376 |
Framework versions
- Transformers 4.50.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.21.1
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Model tree for Hartunka/bert_base_rand_20_v1_cola
Base model
Hartunka/bert_base_rand_20_v1Dataset used to train Hartunka/bert_base_rand_20_v1_cola
Evaluation results
- Matthews Correlation on GLUE COLAself-reported0.029
- Accuracy on GLUE COLAself-reported0.684
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hartunka/bert_base_rand_20_v1_cola")