---
license: mit
base_model: haryoaw/teacher_tweet_eval_sentiment_xlmr_base
tags:
- generated_from_trainer
datasets:
- tweet_eval
metrics:
- accuracy
- f1
model-index:
- name: scenario-kd-from-post-finetune-gold-silver-div-2-data-tweet_eval-sentiment-model
  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. -->

# scenario-kd-from-post-finetune-gold-silver-div-2-data-tweet_eval-sentiment-model

This model is a fine-tuned version of [haryoaw/teacher_tweet_eval_sentiment_xlmr_base](https://huggingface.co/haryoaw/teacher_tweet_eval_sentiment_xlmr_base) on the tweet_eval dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3344
- Accuracy: 0.734
- F1: 0.7061

## 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: 32
- eval_batch_size: 32
- seed: 42
- 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 | F1     |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
| 1.838         | 0.7   | 1000  | 1.8178          | 0.71     | 0.6779 |
| 1.3953        | 1.4   | 2000  | 1.5675          | 0.72     | 0.6988 |
| 1.2818        | 2.1   | 3000  | 1.6086          | 0.7205   | 0.6892 |
| 1.1321        | 2.81  | 4000  | 1.6146          | 0.7235   | 0.7013 |
| 0.9348        | 3.51  | 5000  | 1.6493          | 0.719    | 0.6902 |
| 0.9139        | 4.21  | 6000  | 1.5044          | 0.719    | 0.7026 |
| 0.8836        | 4.91  | 7000  | 1.4467          | 0.728    | 0.7068 |
| 0.7857        | 5.61  | 8000  | 1.4894          | 0.727    | 0.6971 |
| 0.7366        | 6.31  | 9000  | 1.4895          | 0.7265   | 0.7052 |
| 0.7471        | 7.01  | 10000 | 1.4055          | 0.73     | 0.7089 |
| 0.7067        | 7.71  | 11000 | 1.4671          | 0.729    | 0.7055 |
| 0.6668        | 8.42  | 12000 | 1.4966          | 0.729    | 0.7011 |
| 0.6608        | 9.12  | 13000 | 1.4326          | 0.722    | 0.7006 |
| 0.6371        | 9.82  | 14000 | 1.4281          | 0.724    | 0.7005 |
| 0.6047        | 10.52 | 15000 | 1.4260          | 0.7225   | 0.6954 |
| 0.5929        | 11.22 | 16000 | 1.4013          | 0.7235   | 0.6974 |
| 0.5963        | 11.92 | 17000 | 1.3812          | 0.727    | 0.7053 |
| 0.5777        | 12.62 | 18000 | 1.3694          | 0.727    | 0.7029 |
| 0.5587        | 13.32 | 19000 | 1.4384          | 0.724    | 0.6951 |
| 0.5631        | 14.03 | 20000 | 1.3488          | 0.732    | 0.7097 |
| 0.538         | 14.73 | 21000 | 1.3758          | 0.7285   | 0.7042 |
| 0.5365        | 15.43 | 22000 | 1.3314          | 0.7305   | 0.7059 |
| 0.5339        | 16.13 | 23000 | 1.3576          | 0.729    | 0.7046 |
| 0.5232        | 16.83 | 24000 | 1.3652          | 0.732    | 0.7065 |
| 0.5082        | 17.53 | 25000 | 1.4092          | 0.729    | 0.7015 |
| 0.5015        | 18.23 | 26000 | 1.3548          | 0.726    | 0.7019 |
| 0.5035        | 18.93 | 27000 | 1.3637          | 0.7335   | 0.7076 |
| 0.4932        | 19.64 | 28000 | 1.3489          | 0.7205   | 0.6968 |
| 0.4867        | 20.34 | 29000 | 1.3753          | 0.7385   | 0.7135 |
| 0.4819        | 21.04 | 30000 | 1.3652          | 0.727    | 0.7050 |
| 0.4782        | 21.74 | 31000 | 1.3339          | 0.743    | 0.7194 |
| 0.4712        | 22.44 | 32000 | 1.3229          | 0.728    | 0.7059 |
| 0.4677        | 23.14 | 33000 | 1.3203          | 0.7365   | 0.7114 |
| 0.4736        | 23.84 | 34000 | 1.3605          | 0.7345   | 0.7114 |
| 0.4551        | 24.54 | 35000 | 1.3491          | 0.724    | 0.7016 |
| 0.458         | 25.25 | 36000 | 1.3663          | 0.739    | 0.7063 |
| 0.4545        | 25.95 | 37000 | 1.3502          | 0.734    | 0.7087 |
| 0.4471        | 26.65 | 38000 | 1.3435          | 0.7375   | 0.7100 |
| 0.441         | 27.35 | 39000 | 1.3069          | 0.7435   | 0.7155 |
| 0.4495        | 28.05 | 40000 | 1.3175          | 0.7285   | 0.7037 |
| 0.4411        | 28.75 | 41000 | 1.3344          | 0.734    | 0.7061 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1
- Datasets 2.14.5
- Tokenizers 0.13.3