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---
base_model: gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5
tags:
- generated_from_trainer
datasets:
- massive
metrics:
- accuracy
model-index:
- name: hbertv1-massive-logit_KD-tiny_ffn_0.5
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: massive
      type: massive
      config: en-US
      split: validation
      args: en-US
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.8407919331037875
---

<!-- 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. -->

# hbertv1-massive-logit_KD-tiny_ffn_0.5

This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_tiny_freeze_new_ffn_0.5) on the massive dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6585
- Accuracy: 0.8308

## 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: 33
- distributed_type: multi-GPU
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 4.3023        | 1.0   | 180  | 3.8354          | 0.1766   |
| 3.7037        | 2.0   | 360  | 3.2686          | 0.2027   |
| 3.2011        | 3.0   | 540  | 2.8012          | 0.2966   |
| 2.774         | 4.0   | 720  | 2.4055          | 0.3802   |
| 2.4069        | 5.0   | 900  | 2.0833          | 0.4747   |
| 2.1164        | 6.0   | 1080 | 1.8300          | 0.5588   |
| 1.8907        | 7.0   | 1260 | 1.6351          | 0.6252   |
| 1.71          | 8.0   | 1440 | 1.4792          | 0.6621   |
| 1.5648        | 9.0   | 1620 | 1.3605          | 0.6936   |
| 1.4399        | 10.0  | 1800 | 1.2607          | 0.7103   |
| 1.3436        | 11.0  | 1980 | 1.1872          | 0.7201   |
| 1.266         | 12.0  | 2160 | 1.1295          | 0.7285   |
| 1.1934        | 13.0  | 2340 | 1.0829          | 0.7359   |
| 1.1413        | 14.0  | 2520 | 1.0428          | 0.7472   |
| 1.0807        | 15.0  | 2700 | 0.9984          | 0.7585   |
| 1.0382        | 16.0  | 2880 | 0.9693          | 0.7600   |
| 0.9982        | 17.0  | 3060 | 0.9439          | 0.7673   |
| 0.9626        | 18.0  | 3240 | 0.9207          | 0.7723   |
| 0.9299        | 19.0  | 3420 | 0.8887          | 0.7796   |
| 0.8828        | 20.0  | 3600 | 0.8686          | 0.7796   |
| 0.8593        | 21.0  | 3780 | 0.8537          | 0.7905   |
| 0.8329        | 22.0  | 3960 | 0.8250          | 0.7934   |
| 0.8043        | 23.0  | 4140 | 0.8098          | 0.7959   |
| 0.7764        | 24.0  | 4320 | 0.7990          | 0.8008   |
| 0.7569        | 25.0  | 4500 | 0.7823          | 0.8067   |
| 0.7372        | 26.0  | 4680 | 0.7749          | 0.8023   |
| 0.7182        | 27.0  | 4860 | 0.7640          | 0.8101   |
| 0.6987        | 28.0  | 5040 | 0.7509          | 0.8106   |
| 0.6842        | 29.0  | 5220 | 0.7386          | 0.8146   |
| 0.6673        | 30.0  | 5400 | 0.7305          | 0.8146   |
| 0.6509        | 31.0  | 5580 | 0.7196          | 0.8214   |
| 0.6382        | 32.0  | 5760 | 0.7120          | 0.8170   |
| 0.6301        | 33.0  | 5940 | 0.7134          | 0.8190   |
| 0.6139        | 34.0  | 6120 | 0.7062          | 0.8200   |
| 0.6076        | 35.0  | 6300 | 0.6928          | 0.8205   |
| 0.5919        | 36.0  | 6480 | 0.6838          | 0.8244   |
| 0.5792        | 37.0  | 6660 | 0.6819          | 0.8264   |
| 0.5739        | 38.0  | 6840 | 0.6780          | 0.8210   |
| 0.5698        | 39.0  | 7020 | 0.6684          | 0.8283   |
| 0.5602        | 40.0  | 7200 | 0.6692          | 0.8249   |
| 0.5534        | 41.0  | 7380 | 0.6644          | 0.8298   |
| 0.5429        | 42.0  | 7560 | 0.6599          | 0.8278   |
| 0.5423        | 43.0  | 7740 | 0.6585          | 0.8308   |
| 0.5356        | 44.0  | 7920 | 0.6569          | 0.8293   |
| 0.5374        | 45.0  | 8100 | 0.6565          | 0.8293   |
| 0.5327        | 46.0  | 8280 | 0.6540          | 0.8273   |
| 0.5324        | 47.0  | 8460 | 0.6523          | 0.8273   |
| 0.5281        | 48.0  | 8640 | 0.6519          | 0.8283   |


### Framework versions

- Transformers 4.35.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.15.0
- Tokenizers 0.15.0