pytorch safetensors generated_from_trainer base_model:roberta-base license:mit region:us
---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: ghc-roberta-base-intra-sorted-model_annots-cross-ent-batch-size
  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. -->

# ghc-roberta-base-intra-sorted-model_annots-cross-ent-batch-size

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 75.2559

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 150.1364      | 0.01  | 1    | 137.8655        |
| 145.1491      | 0.01  | 2    | 137.7009        |
| 141.2592      | 0.02  | 3    | 137.3692        |
| 139.0919      | 0.02  | 4    | 136.8588        |
| 135.9284      | 0.03  | 5    | 136.1717        |
| 136.926       | 0.03  | 6    | 135.3063        |
| 134.5704      | 0.04  | 7    | 134.2661        |
| 137.4961      | 0.05  | 8    | 133.0658        |
| 132.8797      | 0.05  | 9    | 131.7179        |
| 136.0643      | 0.06  | 10   | 130.2276        |
| 135.4301      | 0.06  | 11   | 128.5899        |
| 127.1964      | 0.07  | 12   | 126.8418        |
| 125.513       | 0.08  | 13   | 124.9421        |
| 126.1663      | 0.08  | 14   | 122.8761        |
| 119.5367      | 0.09  | 15   | 120.6167        |
| 115.1592      | 0.09  | 16   | 118.1486        |
| 119.9518      | 0.1   | 17   | 115.4187        |
| 117.7895      | 0.1   | 18   | 112.3129        |
| 106.805       | 0.11  | 19   | 108.8144        |
| 108.7341      | 0.12  | 20   | 104.8086        |
| 99.3505       | 0.12  | 21   | 100.0166        |
| 96.6034       | 0.13  | 22   | 94.8025         |
| 97.1092       | 0.13  | 23   | 89.3208         |
| 87.4798       | 0.14  | 24   | 83.9749         |
| 84.8475       | 0.14  | 25   | 79.4704         |
| 83.373        | 0.15  | 26   | 77.4992         |
| 91.3204       | 0.16  | 27   | 77.1923         |
| 74.5017       | 0.16  | 28   | 76.8741         |
| 72.3207       | 0.17  | 29   | 76.2473         |
| 85.4136       | 0.17  | 30   | 75.5046         |
| 93.5758       | 0.18  | 31   | 76.7842         |
| 86.1518       | 0.18  | 32   | 80.6888         |
| 81.8937       | 0.19  | 33   | 81.3889         |
| 83.6016       | 0.2   | 34   | 78.7130         |
| 80.4784       | 0.2   | 35   | 75.8756         |
| 78.3552       | 0.21  | 36   | 74.9318         |
| 80.5475       | 0.21  | 37   | 75.4798         |
| 76.2882       | 0.22  | 38   | 76.9049         |
| 84.8002       | 0.23  | 39   | 76.9469         |
| 77.4504       | 0.23  | 40   | 75.8898         |
| 67.6916       | 0.24  | 41   | 75.0978         |
| 83.2207       | 0.24  | 42   | 74.9062         |
| 85.0015       | 0.25  | 43   | 75.6731         |
| 83.0497       | 0.25  | 44   | 75.9090         |
| 76.6919       | 0.26  | 45   | 75.5054         |
| 85.3877       | 0.27  | 46   | 75.1098         |
| 93.0404       | 0.27  | 47   | 74.9389         |
| 84.2074       | 0.28  | 48   | 74.9638         |
| 95.3972       | 0.28  | 49   | 76.3316         |
| 69.0631       | 0.29  | 50   | 77.7318         |
| 75.4309       | 0.29  | 51   | 77.7450         |
| 71.4134       | 0.3   | 52   | 76.5342         |
| 69.1066       | 0.31  | 53   | 77.6628         |
| 83.5769       | 0.31  | 54   | 78.5326         |
| 65.4712       | 0.32  | 55   | 77.5269         |
| 73.439        | 0.32  | 56   | 76.4808         |
| 76.9116       | 0.33  | 57   | 76.2608         |
| 79.1694       | 0.34  | 58   | 75.3286         |
| 73.6838       | 0.34  | 59   | 75.0881         |
| 73.1652       | 0.35  | 60   | 74.1375         |
| 83.7013       | 0.35  | 61   | 74.3447         |
| 84.6303       | 0.36  | 62   | 74.5879         |
| 91.8366       | 0.36  | 63   | 73.4361         |
| 77.6664       | 0.37  | 64   | 72.9986         |
| 79.3617       | 0.38  | 65   | 72.9200         |
| 81.8254       | 0.38  | 66   | 73.0654         |
| 79.6363       | 0.39  | 67   | 73.0463         |
| 86.762        | 0.39  | 68   | 73.1884         |
| 86.3385       | 0.4   | 69   | 73.4171         |
| 84.0979       | 0.4   | 70   | 73.6643         |
| 80.2404       | 0.41  | 71   | 73.6566         |
| 85.6388       | 0.42  | 72   | 73.6430         |
| 74.8952       | 0.42  | 73   | 73.4709         |
| 67.454        | 0.43  | 74   | 73.2007         |
| 77.6211       | 0.43  | 75   | 72.9498         |
| 91.3803       | 0.44  | 76   | 72.5157         |
| 83.2057       | 0.45  | 77   | 73.7496         |
| 78.6635       | 0.45  | 78   | 76.5247         |
| 62.8234       | 0.46  | 79   | 77.4481         |
| 90.3382       | 0.46  | 80   | 76.1735         |
| 79.189        | 0.47  | 81   | 75.0716         |
| 69.5808       | 0.47  | 82   | 76.5869         |
| 73.8021       | 0.48  | 83   | 77.8004         |
| 84.3247       | 0.49  | 84   | 76.7431         |
| 69.6219       | 0.49  | 85   | 75.4564         |
| 74.931        | 0.5   | 86   | 74.4129         |
| 72.8238       | 0.5   | 87   | 74.6309         |
| 72.4519       | 0.51  | 88   | 75.2184         |
| 72.0305       | 0.51  | 89   | 75.1167         |
| 84.3407       | 0.52  | 90   | 74.1608         |
| 82.8978       | 0.53  | 91   | 77.1175         |
| 69.8918       | 0.53  | 92   | 82.0105         |
| 88.752        | 0.54  | 93   | 80.1509         |
| 80.5262       | 0.54  | 94   | 74.2979         |
| 71.7139       | 0.55  | 95   | 72.3956         |
| 77.5043       | 0.55  | 96   | 73.0314         |
| 92.5619       | 0.56  | 97   | 73.5085         |
| 70.4613       | 0.57  | 98   | 74.0224         |
| 83.6026       | 0.57  | 99   | 73.7450         |
| 75.0023       | 0.58  | 100  | 73.0852         |
| 85.3673       | 0.58  | 101  | 73.1021         |
| 83.6135       | 0.59  | 102  | 73.1276         |
| 77.869        | 0.6   | 103  | 73.4371         |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.1.0+cu121
- Datasets 2.6.1
- Tokenizers 0.14.1
