transformers safetensors bert generated_from_trainer base_model:haryoaw/scenario-TCR-data-glue-mnli-model-bert-base-uncased license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: haryoaw/scenario-TCR-data-glue-mnli-model-bert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: scenario-KD-MNLI-H2L2-data-glue-mnli-model-haryoaw-scenario-TCR-data-glue-mnli-m
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# scenario-KD-MNLI-H2L2-data-glue-mnli-model-haryoaw-scenario-TCR-data-glue-mnli-m

This model is a fine-tuned version of [haryoaw/scenario-TCR-data-glue-mnli-model-bert-base-uncased](https://huggingface.co/haryoaw/scenario-TCR-data-glue-mnli-model-bert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2652
- Accuracy: 0.7345

## 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: 32
- seed: 45
- 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: 6969

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 4.7631        | 0.16  | 2000  | 4.2896          | 0.5442   |
| 4.2241        | 0.33  | 4000  | 3.8002          | 0.6130   |
| 3.7351        | 0.49  | 6000  | 3.4852          | 0.6383   |
| 3.421         | 0.65  | 8000  | 3.1054          | 0.6660   |
| 3.2734        | 0.81  | 10000 | 2.9262          | 0.6756   |
| 3.0989        | 0.98  | 12000 | 2.7570          | 0.6847   |
| 2.7703        | 1.14  | 14000 | 2.6783          | 0.6942   |
| 2.7347        | 1.3   | 16000 | 2.6142          | 0.7027   |
| 2.6868        | 1.47  | 18000 | 2.6140          | 0.6967   |
| 2.6515        | 1.63  | 20000 | 2.5840          | 0.7036   |
| 2.6358        | 1.79  | 22000 | 2.4840          | 0.7130   |
| 2.5852        | 1.96  | 24000 | 2.4439          | 0.7093   |
| 2.2099        | 2.12  | 26000 | 2.4247          | 0.7168   |
| 2.1958        | 2.28  | 28000 | 2.4380          | 0.7223   |
| 2.1728        | 2.44  | 30000 | 2.3775          | 0.7178   |
| 2.2362        | 2.61  | 32000 | 2.3434          | 0.7268   |
| 2.2516        | 2.77  | 34000 | 2.3518          | 0.7265   |
| 2.2215        | 2.93  | 36000 | 2.2763          | 0.7276   |
| 1.8359        | 3.1   | 38000 | 2.3938          | 0.7225   |
| 1.8966        | 3.26  | 40000 | 2.3542          | 0.7205   |
| 1.8969        | 3.42  | 42000 | 2.3704          | 0.7232   |
| 1.9009        | 3.59  | 44000 | 2.4391          | 0.7267   |
| 1.9248        | 3.75  | 46000 | 2.2948          | 0.7321   |
| 1.9339        | 3.91  | 48000 | 2.2611          | 0.7351   |
| 1.5694        | 4.07  | 50000 | 2.3303          | 0.7347   |
| 1.6294        | 4.24  | 52000 | 2.3628          | 0.7290   |
| 1.6437        | 4.4   | 54000 | 2.3450          | 0.7329   |
| 1.7035        | 4.56  | 56000 | 2.4139          | 0.7338   |
| 1.7244        | 4.73  | 58000 | 2.2652          | 0.7345   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2
- Datasets 2.16.0
- Tokenizers 0.15.0
