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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- crows_pairs
metrics:
- accuracy
model-index:
- name: multiberts-seed_2-step_2000k_crows_pairs_classifieronly
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: crows_pairs
type: crows_pairs
config: crows_pairs
split: test
args: crows_pairs
metrics:
- name: Accuracy
type: accuracy
value: 0.4602649006622517
---
<!-- 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. -->
# multiberts-seed_2-step_2000k_crows_pairs_classifieronly
This model is a fine-tuned version of [google/multiberts-seed_2-step_2000k](https://huggingface.co/google/multiberts-seed_2-step_2000k) on the crows_pairs dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6970
- Accuracy: 0.4603
- Tp: 0.2748
- Tn: 0.1854
- Fp: 0.3013
- Fn: 0.2384
## 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: 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 | Accuracy | Tp | Tn | Fp | Fn |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:------:|:------:|
| 0.7105 | 1.05 | 20 | 0.6958 | 0.4934 | 0.4404 | 0.0530 | 0.4338 | 0.0728 |
| 0.7148 | 2.11 | 40 | 0.6962 | 0.4801 | 0.2020 | 0.2781 | 0.2086 | 0.3113 |
| 0.7057 | 3.16 | 60 | 0.6972 | 0.4536 | 0.0695 | 0.3841 | 0.1026 | 0.4437 |
| 0.6938 | 4.21 | 80 | 0.6966 | 0.5099 | 0.5 | 0.0099 | 0.4768 | 0.0132 |
| 0.7029 | 5.26 | 100 | 0.6993 | 0.4801 | 0.0166 | 0.4636 | 0.0232 | 0.4967 |
| 0.696 | 6.32 | 120 | 0.6961 | 0.4901 | 0.4536 | 0.0364 | 0.4503 | 0.0596 |
| 0.6999 | 7.37 | 140 | 0.6971 | 0.4305 | 0.0762 | 0.3543 | 0.1325 | 0.4371 |
| 0.7079 | 8.42 | 160 | 0.6963 | 0.4702 | 0.2252 | 0.2450 | 0.2417 | 0.2881 |
| 0.7038 | 9.47 | 180 | 0.6960 | 0.5033 | 0.4007 | 0.1026 | 0.3841 | 0.1126 |
| 0.6914 | 10.53 | 200 | 0.6966 | 0.4768 | 0.1954 | 0.2815 | 0.2053 | 0.3179 |
| 0.696 | 11.58 | 220 | 0.6962 | 0.5033 | 0.4404 | 0.0629 | 0.4238 | 0.0728 |
| 0.7009 | 12.63 | 240 | 0.6983 | 0.4669 | 0.0530 | 0.4139 | 0.0728 | 0.4603 |
| 0.7062 | 13.68 | 260 | 0.6965 | 0.4669 | 0.3013 | 0.1656 | 0.3212 | 0.2119 |
| 0.6966 | 14.74 | 280 | 0.6990 | 0.4868 | 0.0364 | 0.4503 | 0.0364 | 0.4768 |
| 0.7038 | 15.79 | 300 | 0.6975 | 0.5 | 0.4934 | 0.0066 | 0.4801 | 0.0199 |
| 0.7031 | 16.84 | 320 | 0.6964 | 0.5033 | 0.3974 | 0.1060 | 0.3808 | 0.1159 |
| 0.7032 | 17.89 | 340 | 0.6965 | 0.4801 | 0.3311 | 0.1490 | 0.3377 | 0.1821 |
| 0.7004 | 18.95 | 360 | 0.6990 | 0.4868 | 0.0364 | 0.4503 | 0.0364 | 0.4768 |
| 0.695 | 20.0 | 380 | 0.6966 | 0.4636 | 0.2715 | 0.1921 | 0.2947 | 0.2417 |
| 0.7052 | 21.05 | 400 | 0.6974 | 0.4338 | 0.1126 | 0.3212 | 0.1656 | 0.4007 |
| 0.6995 | 22.11 | 420 | 0.6965 | 0.4934 | 0.3642 | 0.1291 | 0.3576 | 0.1490 |
| 0.714 | 23.16 | 440 | 0.6971 | 0.4868 | 0.1821 | 0.3046 | 0.1821 | 0.3311 |
| 0.7004 | 24.21 | 460 | 0.6980 | 0.4536 | 0.0596 | 0.3940 | 0.0927 | 0.4536 |
| 0.7025 | 25.26 | 480 | 0.6966 | 0.4801 | 0.3344 | 0.1457 | 0.3411 | 0.1788 |
| 0.6987 | 26.32 | 500 | 0.6975 | 0.4404 | 0.1093 | 0.3311 | 0.1556 | 0.4040 |
| 0.6956 | 27.37 | 520 | 0.6975 | 0.4470 | 0.1291 | 0.3179 | 0.1689 | 0.3841 |
| 0.697 | 28.42 | 540 | 0.6974 | 0.4570 | 0.1424 | 0.3146 | 0.1722 | 0.3709 |
| 0.7051 | 29.47 | 560 | 0.6975 | 0.4536 | 0.1358 | 0.3179 | 0.1689 | 0.3775 |
| 0.7024 | 30.53 | 580 | 0.6979 | 0.4338 | 0.0828 | 0.3510 | 0.1358 | 0.4305 |
| 0.6908 | 31.58 | 600 | 0.6969 | 0.4636 | 0.2682 | 0.1954 | 0.2914 | 0.2450 |
| 0.6979 | 32.63 | 620 | 0.6970 | 0.4868 | 0.2583 | 0.2285 | 0.2583 | 0.2550 |
| 0.7026 | 33.68 | 640 | 0.6970 | 0.4834 | 0.2583 | 0.2252 | 0.2616 | 0.2550 |
| 0.6998 | 34.74 | 660 | 0.6970 | 0.4834 | 0.2583 | 0.2252 | 0.2616 | 0.2550 |
| 0.6964 | 35.79 | 680 | 0.6969 | 0.4669 | 0.2682 | 0.1987 | 0.2881 | 0.2450 |
| 0.709 | 36.84 | 700 | 0.6968 | 0.4868 | 0.3510 | 0.1358 | 0.3510 | 0.1623 |
| 0.6974 | 37.89 | 720 | 0.6969 | 0.4669 | 0.2881 | 0.1788 | 0.3079 | 0.2252 |
| 0.7039 | 38.95 | 740 | 0.6972 | 0.4934 | 0.2318 | 0.2616 | 0.2252 | 0.2815 |
| 0.6963 | 40.0 | 760 | 0.6970 | 0.4768 | 0.2715 | 0.2053 | 0.2815 | 0.2417 |
| 0.6891 | 41.05 | 780 | 0.6970 | 0.4801 | 0.2682 | 0.2119 | 0.2748 | 0.2450 |
| 0.7008 | 42.11 | 800 | 0.6969 | 0.4868 | 0.3245 | 0.1623 | 0.3245 | 0.1887 |
| 0.7026 | 43.16 | 820 | 0.6971 | 0.4934 | 0.2550 | 0.2384 | 0.2483 | 0.2583 |
| 0.6969 | 44.21 | 840 | 0.6974 | 0.4834 | 0.1821 | 0.3013 | 0.1854 | 0.3311 |
| 0.7057 | 45.26 | 860 | 0.6972 | 0.4967 | 0.2285 | 0.2682 | 0.2185 | 0.2848 |
| 0.6951 | 46.32 | 880 | 0.6971 | 0.4901 | 0.2550 | 0.2351 | 0.2517 | 0.2583 |
| 0.7041 | 47.37 | 900 | 0.6969 | 0.4934 | 0.3311 | 0.1623 | 0.3245 | 0.1821 |
| 0.7019 | 48.42 | 920 | 0.6969 | 0.4768 | 0.3046 | 0.1722 | 0.3146 | 0.2086 |
| 0.6998 | 49.47 | 940 | 0.6970 | 0.4603 | 0.2748 | 0.1854 | 0.3013 | 0.2384 |
### Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2
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