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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Job_compatibility_model
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# Job_compatibility_model
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6238
- Accuracy: 0.8598
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 25
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 32 | 0.6922 | 0.5 |
| No log | 2.0 | 64 | 0.6509 | 0.6238 |
| No log | 3.0 | 96 | 0.4218 | 0.8411 |
| No log | 4.0 | 128 | 0.3622 | 0.8481 |
| No log | 5.0 | 160 | 0.3383 | 0.8645 |
| No log | 6.0 | 192 | 0.3626 | 0.8528 |
| No log | 7.0 | 224 | 0.3939 | 0.8621 |
| No log | 8.0 | 256 | 0.4223 | 0.8715 |
| No log | 9.0 | 288 | 0.4271 | 0.8692 |
| No log | 10.0 | 320 | 0.4869 | 0.8621 |
| No log | 11.0 | 352 | 0.5057 | 0.8645 |
| No log | 12.0 | 384 | 0.5702 | 0.8528 |
| No log | 13.0 | 416 | 0.5277 | 0.8692 |
| No log | 14.0 | 448 | 0.5228 | 0.8785 |
| No log | 15.0 | 480 | 0.5332 | 0.8762 |
| 0.2235 | 16.0 | 512 | 0.5859 | 0.8715 |
| 0.2235 | 17.0 | 544 | 0.5938 | 0.8762 |
| 0.2235 | 18.0 | 576 | 0.6005 | 0.8715 |
| 0.2235 | 19.0 | 608 | 0.5941 | 0.8715 |
| 0.2235 | 20.0 | 640 | 0.6115 | 0.8762 |
| 0.2235 | 21.0 | 672 | 0.6098 | 0.8715 |
| 0.2235 | 22.0 | 704 | 0.6091 | 0.8715 |
| 0.2235 | 23.0 | 736 | 0.6223 | 0.8621 |
| 0.2235 | 24.0 | 768 | 0.6309 | 0.8598 |
| 0.2235 | 25.0 | 800 | 0.6238 | 0.8598 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2
|