---
license: cc-by-4.0
base_model: allegro/herbert-large-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: herbert-large-cased_nli
  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. -->

# herbert-large-cased_nli

This model is a fine-tuned version of [allegro/herbert-large-cased](https://huggingface.co/allegro/herbert-large-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0905
- Accuracy: 0.77

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| No log        | 1.0   | 625   | 0.6466          | 0.751    |
| No log        | 2.0   | 1250  | 0.5856          | 0.79     |
| 0.5915        | 3.0   | 1875  | 0.6142          | 0.761    |
| 0.5915        | 4.0   | 2500  | 0.6803          | 0.78     |
| 0.4204        | 5.0   | 3125  | 0.7207          | 0.786    |
| 0.4204        | 6.0   | 3750  | 0.7956          | 0.777    |
| 0.4204        | 7.0   | 4375  | 0.7964          | 0.787    |
| 0.306         | 8.0   | 5000  | 0.7869          | 0.766    |
| 0.306         | 9.0   | 5625  | 0.8671          | 0.766    |
| 0.2192        | 10.0  | 6250  | 0.8832          | 0.778    |
| 0.2192        | 11.0  | 6875  | 0.9147          | 0.768    |
| 0.1595        | 12.0  | 7500  | 1.1113          | 0.756    |
| 0.1595        | 13.0  | 8125  | 1.0984          | 0.761    |
| 0.1595        | 14.0  | 8750  | 1.3107          | 0.758    |
| 0.1288        | 15.0  | 9375  | 1.2892          | 0.764    |
| 0.1288        | 16.0  | 10000 | 1.5291          | 0.741    |
| 0.1037        | 17.0  | 10625 | 1.2105          | 0.786    |
| 0.1037        | 18.0  | 11250 | 1.3468          | 0.78     |
| 0.1037        | 19.0  | 11875 | 1.5642          | 0.758    |
| 0.0864        | 20.0  | 12500 | 1.5304          | 0.768    |
| 0.0864        | 21.0  | 13125 | 1.4310          | 0.776    |
| 0.0728        | 22.0  | 13750 | 1.5636          | 0.762    |
| 0.0728        | 23.0  | 14375 | 1.5032          | 0.766    |
| 0.0583        | 24.0  | 15000 | 1.7275          | 0.763    |
| 0.0583        | 25.0  | 15625 | 1.6669          | 0.758    |
| 0.0583        | 26.0  | 16250 | 1.6029          | 0.767    |
| 0.0453        | 27.0  | 16875 | 1.6239          | 0.771    |
| 0.0453        | 28.0  | 17500 | 1.6007          | 0.781    |
| 0.0335        | 29.0  | 18125 | 1.7028          | 0.766    |
| 0.0335        | 30.0  | 18750 | 1.8058          | 0.776    |
| 0.0335        | 31.0  | 19375 | 1.7894          | 0.766    |
| 0.0267        | 32.0  | 20000 | 1.8930          | 0.765    |
| 0.0267        | 33.0  | 20625 | 1.8582          | 0.775    |
| 0.022         | 34.0  | 21250 | 1.9610          | 0.764    |
| 0.022         | 35.0  | 21875 | 2.0128          | 0.775    |
| 0.0163        | 36.0  | 22500 | 2.0248          | 0.773    |
| 0.0163        | 37.0  | 23125 | 2.0203          | 0.77     |
| 0.0163        | 38.0  | 23750 | 2.0615          | 0.77     |
| 0.0115        | 39.0  | 24375 | 2.0787          | 0.769    |
| 0.0115        | 40.0  | 25000 | 2.0905          | 0.77     |


### Framework versions

- Transformers 4.39.3
- Pytorch 1.11.0a0+17540c5
- Datasets 2.20.0
- Tokenizers 0.15.2