---
library_name: transformers
license: mit
base_model: albert/albert-base-v2
tags:
- generated_from_trainer
model-index:
- name: ATSC-albert-base-v2-For-SemEval-2014-Task-4
  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. -->

# ATSC-albert-base-v2-For-SemEval-2014-Task-4

This model is a fine-tuned version of [albert/albert-base-v2](https://huggingface.co/albert/albert-base-v2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0392
- Accurancy: 0.8490

## 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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed:
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 54

### Training results

| Epoch | Training Loss | Validation Loss | Accuracy |
|:-----:|:-------------:|:---------------:|:--------:|
| 1     | 0.8649        | 0.8954          | 0.6497   |
| 2     | 0.6734        | 0.5684          | 0.7775   |
| 3     | 0.5461        | 0.4641          | 0.8097   |
| 4     | 0.4142        | 0.4540          | 0.8275   |
| 5     | 0.3211        | 0.5946          | 0.8034   |
| 6     | 0.2437        | 0.4974          | 0.8329   |
| 7     | 0.1958        | 0.4916          | 0.8168   |
| 8     | 0.1601        | 0.6348          | 0.8275   |
| 9     | 0.1095        | 0.6533          | 0.8293   |
| 10    | 0.0885        | 0.7212          | 0.8204   |
| 11    | 0.0714        | 0.7217          | 0.8240   |
| 12    | 0.0597        | 0.7698          | 0.8266   |
| 13    | 0.0420        | 0.7946          | 0.8400   |
| 14    | 0.0566        | 0.8103          | 0.8418   |
| 15    | 0.0389        | 0.9175          | 0.8275   |
| 16    | 0.0357        | 1.1165          | 0.8266   |
| 17    | 0.0205        | 1.0199          | 0.8302   |
| 18    | 0.0207        | 0.9885          | 0.8391   |
| 19    | 0.0155        | 1.0372          | 0.8374   |
| 20    | 0.0250        | 1.1147          | 0.8365   |
| 21    | 0.0198        | 1.0150          | 0.8472   |
| 22    | 0.0210        | 1.1716          | 0.8356   |
| 23    | 0.0208        | 1.0894          | 0.8454   |
| 24    | 0.0222        | 1.1699          | 0.8382   |
| 25    | 0.0196        | 1.2378          | 0.8338   |
| 26    | 0.0166        | 0.9921          | 0.8490   |
| 27    | 0.0115        | 1.0392          | 0.8490   |
| 28    | 0.0126        | 1.3480          | 0.8311   |
| 29    | 0.0107        | 1.2037          | 0.8427   |
| 30    | 0.0128        | 1.0996          | 0.8427   |
| 31    | 0.0128        | 1.1347          | 0.8320   |
| 32    | 0.0088        | 1.2735          | 0.8356   |
| 33    | 0.0083        | 1.2403          | 0.8409   |
| 34    | 0.0094        | 1.2600          | 0.8418   |
| 35    | 0.0072        | 1.2430          | 0.8454   |
| 36    | 0.0106        | 1.2740          | 0.8391   |
| 37    | 0.0093        | 1.1836          | 0.8427   |
| 38    | 0.0074        | 1.2132          | 0.8454   |
| 39    | 0.0071        | 1.1983          | 0.8463   |
| 40    | 0.0062        | 1.2708          | 0.8409   |
| 41    | 0.0068        | 1.2093          | 0.8463   |
| 42    | 0.0055        | 1.2593          | 0.8445   |
| 43    | 0.0055        | 1.2497          | 0.8445   |
| 44    | 0.0055        | 1.2530          | 0.8463   |
| 45    | 0.0051        | 1.2546          | 0.8463   |
| 46    | 0.0052        | 1.2513          | 0.8463   |
| 47    | 0.0054        | 1.2679          | 0.8481   |
| 48    | 0.0053        | 1.2839          | 0.8463   |
| 49    | 0.0048        | 1.2922          | 0.8445   |
| 50    | 0.0050        | 1.3092          | 0.8409   |
| 51    | 0.0052        | 1.2977          | 0.8436   |
| 52    | 0.0051        | 1.3066          | 0.8427   |
| 53    | 0.0051        | 1.3056          | 0.8436   |
| 54    | 0.0001        | 1.3047          | 0.8436   |



### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0