Tienle123/distilbert-base-uncased-finetuned-emotion
By Tienle123 · ↓ 4 · ♥ 0 · Updated 2025-02-07
What's in this repo
This page lists the files in Tienle123/distilbert-base-uncased-finetuned-emotion, including model.onnx.
- 1 ONNX models (.onnx files)
- 10 files, including 4 .json, 1 .md, 1 .safetensors, 1 .onnx, 1 .bin, 1 .txt
- Last updated 2025-02-07
ONNX files
| File | Size | Download |
|---|---|---|
| onnx/model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
distilbert-base-uncased-finetuned-emotion
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2436
- Accuracy: 0.932
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: 2e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.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: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 125 | 0.2455 | 0.9315 |
| No log | 2.0 | 250 | 0.2436 | 0.932 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
Model info
Created: 2025-02-06
Updated: 2025-02-07
View on Hugging Face