Text Classification
Transformers
TensorBoard
Safetensors
bert
Generated from Trainer
text-embeddings-inference
Instructions to use MehdiHosseiniMoghadam/all-MiniLM-L6-v2-finetuned-marc-en with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MehdiHosseiniMoghadam/all-MiniLM-L6-v2-finetuned-marc-en with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MehdiHosseiniMoghadam/all-MiniLM-L6-v2-finetuned-marc-en")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MehdiHosseiniMoghadam/all-MiniLM-L6-v2-finetuned-marc-en") model = AutoModelForSequenceClassification.from_pretrained("MehdiHosseiniMoghadam/all-MiniLM-L6-v2-finetuned-marc-en") - Notebooks
- Google Colab
- Kaggle
all-MiniLM-L6-v2-finetuned-marc-en
This model is a fine-tuned version of sentence-transformers/all-MiniLM-L6-v2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8379
- Mae: 2.1394
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: 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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Mae |
|---|---|---|---|---|
| 1.9203 | 1.0 | 250 | 1.8916 | 2.2446 |
| 1.8419 | 2.0 | 500 | 1.8713 | 2.2371 |
| 1.8385 | 3.0 | 750 | 1.8523 | 2.1957 |
| 1.8256 | 4.0 | 1000 | 1.8422 | 2.1584 |
| 1.7618 | 5.0 | 1250 | 1.8339 | 2.1625 |
| 1.8025 | 6.0 | 1500 | 1.8326 | 2.1564 |
| 1.7414 | 7.0 | 1750 | 1.8329 | 2.1629 |
| 1.7539 | 8.0 | 2000 | 1.8322 | 2.173 |
| 1.7886 | 9.0 | 2250 | 1.8290 | 2.16 |
| 1.7611 | 10.0 | 2500 | 1.8292 | 2.1456 |
| 1.7339 | 11.0 | 2750 | 1.8324 | 2.1566 |
| 1.7093 | 12.0 | 3000 | 1.8366 | 2.1406 |
| 1.7164 | 13.0 | 3250 | 1.8371 | 2.1391 |
| 1.6847 | 14.0 | 3500 | 1.8389 | 2.139 |
| 1.7202 | 15.0 | 3750 | 1.8379 | 2.1394 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for MehdiHosseiniMoghadam/all-MiniLM-L6-v2-finetuned-marc-en
Base model
nreimers/MiniLM-L6-H384-uncased Quantized
sentence-transformers/all-MiniLM-L6-v2