---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
metrics:
- accuracy
base_model: google/flan-t5-base
model-index:
- name: emotions_flan_tf
  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. -->

# emotions_flan_tf

This model is a fine-tuned version of [google/flan-t5-base](https://huggingface.co/google/flan-t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4970
- F1 Micro: 0.6980
- F1 Macro: 0.6126
- Accuracy: 0.2188

## 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: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.8313        | 0.21  | 20   | 0.7916          | 0.4215   | 0.1586   | 0.0123   |
| 0.7813        | 0.41  | 40   | 0.7840          | 0.4717   | 0.2286   | 0.0201   |
| 0.7702        | 0.62  | 60   | 0.7485          | 0.4935   | 0.2379   | 0.0971   |
| 0.7218        | 0.83  | 80   | 0.6327          | 0.6045   | 0.3866   | 0.1256   |
| 0.6401        | 1.03  | 100  | 0.5907          | 0.6269   | 0.4310   | 0.1586   |
| 0.5951        | 1.24  | 120  | 0.5668          | 0.6459   | 0.4981   | 0.1502   |
| 0.5686        | 1.45  | 140  | 0.5458          | 0.6593   | 0.5372   | 0.1683   |
| 0.5576        | 1.65  | 160  | 0.5332          | 0.6675   | 0.5403   | 0.1722   |
| 0.5465        | 1.86  | 180  | 0.5224          | 0.6734   | 0.5667   | 0.1812   |
| 0.5436        | 2.07  | 200  | 0.5164          | 0.6807   | 0.5751   | 0.1877   |
| 0.5297        | 2.27  | 220  | 0.5149          | 0.6742   | 0.5793   | 0.1741   |
| 0.5109        | 2.48  | 240  | 0.5049          | 0.6845   | 0.5824   | 0.1929   |
| 0.5265        | 2.69  | 260  | 0.5070          | 0.6846   | 0.5859   | 0.1799   |
| 0.5028        | 2.89  | 280  | 0.5068          | 0.6847   | 0.5870   | 0.1864   |
| 0.5097        | 3.1   | 300  | 0.5025          | 0.6892   | 0.5940   | 0.2084   |
| 0.4971        | 3.31  | 320  | 0.5032          | 0.6843   | 0.5995   | 0.1890   |
| 0.4762        | 3.51  | 340  | 0.5069          | 0.6955   | 0.5928   | 0.2129   |
| 0.4811        | 3.72  | 360  | 0.4954          | 0.6898   | 0.5996   | 0.2026   |
| 0.5065        | 3.93  | 380  | 0.4961          | 0.6918   | 0.6038   | 0.1838   |
| 0.4746        | 4.13  | 400  | 0.4992          | 0.6956   | 0.6009   | 0.2142   |
| 0.4786        | 4.34  | 420  | 0.5013          | 0.6918   | 0.6018   | 0.2026   |
| 0.4832        | 4.55  | 440  | 0.4935          | 0.6904   | 0.6031   | 0.2155   |
| 0.465         | 4.75  | 460  | 0.4984          | 0.6938   | 0.6027   | 0.2071   |
| 0.4683        | 4.96  | 480  | 0.4977          | 0.6960   | 0.6011   | 0.2091   |
| 0.4573        | 5.17  | 500  | 0.4985          | 0.6915   | 0.6076   | 0.2006   |
| 0.4619        | 5.37  | 520  | 0.4952          | 0.6945   | 0.6044   | 0.2129   |
| 0.4535        | 5.58  | 540  | 0.4983          | 0.6927   | 0.6024   | 0.2078   |
| 0.4475        | 5.79  | 560  | 0.4967          | 0.6970   | 0.6064   | 0.2194   |
| 0.454         | 5.99  | 580  | 0.5027          | 0.6941   | 0.6090   | 0.1994   |
| 0.4479        | 6.2   | 600  | 0.4940          | 0.6919   | 0.6041   | 0.2117   |
| 0.4304        | 6.41  | 620  | 0.5002          | 0.6982   | 0.6114   | 0.2006   |
| 0.445         | 6.61  | 640  | 0.4970          | 0.6951   | 0.6098   | 0.2071   |
| 0.4434        | 6.82  | 660  | 0.4964          | 0.6976   | 0.6075   | 0.2136   |
| 0.4543        | 7.03  | 680  | 0.4904          | 0.6936   | 0.6086   | 0.2013   |
| 0.4474        | 7.24  | 700  | 0.4969          | 0.6960   | 0.6108   | 0.2071   |
| 0.4325        | 7.44  | 720  | 0.4998          | 0.7013   | 0.6123   | 0.2123   |
| 0.4362        | 7.65  | 740  | 0.4947          | 0.6953   | 0.6101   | 0.2091   |
| 0.4276        | 7.86  | 760  | 0.4978          | 0.6955   | 0.6119   | 0.2052   |
| 0.4392        | 8.06  | 780  | 0.4944          | 0.6967   | 0.6078   | 0.2104   |
| 0.4167        | 8.27  | 800  | 0.4987          | 0.6966   | 0.6080   | 0.2097   |
| 0.4309        | 8.48  | 820  | 0.4970          | 0.6980   | 0.6126   | 0.2188   |
| 0.42          | 8.68  | 840  | 0.4999          | 0.6977   | 0.6105   | 0.2129   |
| 0.423         | 8.89  | 860  | 0.5003          | 0.6975   | 0.6087   | 0.2142   |
| 0.4382        | 9.1   | 880  | 0.4977          | 0.6975   | 0.6115   | 0.2136   |
| 0.4182        | 9.3   | 900  | 0.4976          | 0.6981   | 0.6123   | 0.2155   |
| 0.4153        | 9.51  | 920  | 0.5000          | 0.6978   | 0.6108   | 0.2175   |
| 0.4277        | 9.72  | 940  | 0.5003          | 0.6982   | 0.6092   | 0.2168   |
| 0.4246        | 9.92  | 960  | 0.5000          | 0.6976   | 0.6093   | 0.2168   |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2