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# dit_maveriq_tobacco3482_2023-07-04

This model is a fine-tuned version of [microsoft/dit-base](https://huggingface.co/microsoft/dit-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2641
- Accuracy: 0.955

## 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: 16
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.96  | 3    | 2.0434          | 0.265    |
| No log        | 1.96  | 6    | 1.9976          | 0.31     |
| No log        | 2.96  | 9    | 1.7970          | 0.335    |
| No log        | 3.96  | 12   | 1.6899          | 0.385    |
| No log        | 4.96  | 15   | 1.6519          | 0.36     |
| No log        | 5.96  | 18   | 1.5378          | 0.42     |
| No log        | 6.96  | 21   | 1.4401          | 0.51     |
| No log        | 7.96  | 24   | 1.3607          | 0.575    |
| No log        | 8.96  | 27   | 1.2614          | 0.605    |
| No log        | 9.96  | 30   | 1.1654          | 0.63     |
| No log        | 10.96 | 33   | 1.0758          | 0.66     |
| No log        | 11.96 | 36   | 0.9908          | 0.73     |
| No log        | 12.96 | 39   | 0.9152          | 0.72     |
| No log        | 13.96 | 42   | 0.8412          | 0.755    |
| No log        | 14.96 | 45   | 0.7759          | 0.78     |
| No log        | 15.96 | 48   | 0.7105          | 0.785    |
| No log        | 16.96 | 51   | 0.6489          | 0.815    |
| No log        | 17.96 | 54   | 0.6037          | 0.825    |
| No log        | 18.96 | 57   | 0.5628          | 0.83     |
| No log        | 19.96 | 60   | 0.5084          | 0.84     |
| No log        | 20.96 | 63   | 0.4593          | 0.85     |
| No log        | 21.96 | 66   | 0.4306          | 0.865    |
| No log        | 22.96 | 69   | 0.4078          | 0.87     |
| No log        | 23.96 | 72   | 0.3888          | 0.875    |
| No log        | 24.96 | 75   | 0.3713          | 0.885    |
| No log        | 25.96 | 78   | 0.3469          | 0.89     |
| No log        | 26.96 | 81   | 0.3234          | 0.91     |
| No log        | 27.96 | 84   | 0.3146          | 0.905    |
| No log        | 28.96 | 87   | 0.3311          | 0.895    |
| No log        | 29.96 | 90   | 0.3178          | 0.92     |
| No log        | 30.96 | 93   | 0.3011          | 0.92     |
| No log        | 31.96 | 96   | 0.2922          | 0.93     |
| No log        | 32.96 | 99   | 0.2822          | 0.93     |
| No log        | 33.96 | 102  | 0.2615          | 0.93     |
| No log        | 34.96 | 105  | 0.2577          | 0.94     |
| No log        | 35.96 | 108  | 0.2587          | 0.94     |
| No log        | 36.96 | 111  | 0.2659          | 0.93     |
| No log        | 37.96 | 114  | 0.2697          | 0.925    |
| No log        | 38.96 | 117  | 0.2721          | 0.93     |
| No log        | 39.96 | 120  | 0.2829          | 0.935    |
| No log        | 40.96 | 123  | 0.2564          | 0.94     |
| No log        | 41.96 | 126  | 0.2420          | 0.94     |
| No log        | 42.96 | 129  | 0.2433          | 0.94     |
| No log        | 43.96 | 132  | 0.2405          | 0.945    |
| No log        | 44.96 | 135  | 0.2391          | 0.95     |
| No log        | 45.96 | 138  | 0.2455          | 0.955    |
| No log        | 46.96 | 141  | 0.2563          | 0.945    |
| No log        | 47.96 | 144  | 0.2653          | 0.95     |
| No log        | 48.96 | 147  | 0.2608          | 0.945    |
| No log        | 49.96 | 150  | 0.2477          | 0.95     |
| No log        | 50.96 | 153  | 0.2443          | 0.95     |
| No log        | 51.96 | 156  | 0.2418          | 0.95     |
| No log        | 52.96 | 159  | 0.2403          | 0.94     |
| No log        | 53.96 | 162  | 0.2384          | 0.945    |
| No log        | 54.96 | 165  | 0.2413          | 0.95     |
| No log        | 55.96 | 168  | 0.2428          | 0.96     |
| No log        | 56.96 | 171  | 0.2409          | 0.955    |
| No log        | 57.96 | 174  | 0.2457          | 0.95     |
| No log        | 58.96 | 177  | 0.2488          | 0.95     |
| No log        | 59.96 | 180  | 0.2548          | 0.955    |
| No log        | 60.96 | 183  | 0.2597          | 0.955    |
| No log        | 61.96 | 186  | 0.2647          | 0.955    |
| No log        | 62.96 | 189  | 0.2651          | 0.955    |
| No log        | 63.96 | 192  | 0.2638          | 0.955    |
| No log        | 64.96 | 195  | 0.2638          | 0.955    |
| No log        | 65.96 | 198  | 0.2664          | 0.955    |
| No log        | 66.96 | 201  | 0.2712          | 0.95     |
| No log        | 67.96 | 204  | 0.2677          | 0.955    |
| No log        | 68.96 | 207  | 0.2601          | 0.95     |
| No log        | 69.96 | 210  | 0.2559          | 0.95     |
| No log        | 70.96 | 213  | 0.2566          | 0.95     |
| No log        | 71.96 | 216  | 0.2611          | 0.95     |
| No log        | 72.96 | 219  | 0.2702          | 0.95     |
| No log        | 73.96 | 222  | 0.2806          | 0.945    |
| No log        | 74.96 | 225  | 0.2842          | 0.945    |
| No log        | 75.96 | 228  | 0.2807          | 0.945    |
| No log        | 76.96 | 231  | 0.2750          | 0.95     |
| No log        | 77.96 | 234  | 0.2656          | 0.955    |
| No log        | 78.96 | 237  | 0.2582          | 0.96     |
| No log        | 79.96 | 240  | 0.2545          | 0.96     |
| No log        | 80.96 | 243  | 0.2535          | 0.96     |
| No log        | 81.96 | 246  | 0.2512          | 0.96     |
| No log        | 82.96 | 249  | 0.2520          | 0.96     |
| No log        | 83.96 | 252  | 0.2546          | 0.96     |
| No log        | 84.96 | 255  | 0.2570          | 0.96     |
| No log        | 85.96 | 258  | 0.2608          | 0.96     |
| No log        | 86.96 | 261  | 0.2641          | 0.96     |
| No log        | 87.96 | 264  | 0.2672          | 0.955    |
| No log        | 88.96 | 267  | 0.2686          | 0.955    |
| No log        | 89.96 | 270  | 0.2682          | 0.955    |
| No log        | 90.96 | 273  | 0.2671          | 0.955    |
| No log        | 91.96 | 276  | 0.2652          | 0.96     |
| No log        | 92.96 | 279  | 0.2639          | 0.96     |
| No log        | 93.96 | 282  | 0.2635          | 0.96     |
| No log        | 94.96 | 285  | 0.2633          | 0.96     |
| No log        | 95.96 | 288  | 0.2635          | 0.955    |
| No log        | 96.96 | 291  | 0.2636          | 0.955    |
| No log        | 97.96 | 294  | 0.2639          | 0.955    |
| No log        | 98.96 | 297  | 0.2640          | 0.955    |
| No log        | 99.96 | 300  | 0.2641          | 0.955    |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.1.post200
- Datasets 2.9.0
- Tokenizers 0.13.2

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