Text Classification
Transformers
TensorBoard
Safetensors
English
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Hartunka/tiny_bert_rand_5_v2_sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/tiny_bert_rand_5_v2_sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Hartunka/tiny_bert_rand_5_v2_sst2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Hartunka/tiny_bert_rand_5_v2_sst2") model = AutoModelForSequenceClassification.from_pretrained("Hartunka/tiny_bert_rand_5_v2_sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 228 Bytes
9004e41 | 1 2 3 4 5 6 7 8 9 | {
"epoch": 6.0,
"eval_accuracy": 0.8165137614678899,
"eval_loss": 0.44867685437202454,
"eval_runtime": 0.2878,
"eval_samples": 872,
"eval_samples_per_second": 3030.185,
"eval_steps_per_second": 13.9
} |