readme: ---
  tags:
  - generated_from_trainer
  datasets:
  - becasv2
  model-index:
  - name: legalectra-small-spanish-becasv3-6
    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. -->
  
  # legalectra-small-spanish-becasv3-6
  
  This model is a fine-tuned version of [mrm8488/legalectra-small-spanish](https://huggingface.co/mrm8488/legalectra-small-spanish) on the becasv2 dataset.
  It achieves the following results on the evaluation set:
  - Loss: 3.8441
  
  ## 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: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 150
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | No log        | 1.0   | 5    | 5.6469          |
  | No log        | 2.0   | 10   | 5.5104          |
  | No log        | 3.0   | 15   | 5.4071          |
  | No log        | 4.0   | 20   | 5.3313          |
  | No log        | 5.0   | 25   | 5.2629          |
  | No log        | 6.0   | 30   | 5.1972          |
  | No log        | 7.0   | 35   | 5.1336          |
  | No log        | 8.0   | 40   | 5.0667          |
  | No log        | 9.0   | 45   | 5.0030          |
  | No log        | 10.0  | 50   | 4.9302          |
  | No log        | 11.0  | 55   | 4.8646          |
  | No log        | 12.0  | 60   | 4.7963          |
  | No log        | 13.0  | 65   | 4.7328          |
  | No log        | 14.0  | 70   | 4.6735          |
  | No log        | 15.0  | 75   | 4.6258          |
  | No log        | 16.0  | 80   | 4.5869          |
  | No log        | 17.0  | 85   | 4.5528          |
  | No log        | 18.0  | 90   | 4.5177          |
  | No log        | 19.0  | 95   | 4.4916          |
  | No log        | 20.0  | 100  | 4.4685          |
  | No log        | 21.0  | 105  | 4.4371          |
  | No log        | 22.0  | 110  | 4.4271          |
  | No log        | 23.0  | 115  | 4.3905          |
  | No log        | 24.0  | 120  | 4.3931          |
  | No log        | 25.0  | 125  | 4.3902          |
  | No log        | 26.0  | 130  | 4.3772          |
  | No log        | 27.0  | 135  | 4.3981          |
  | No log        | 28.0  | 140  | 4.4463          |
  | No log        | 29.0  | 145  | 4.4501          |
  | No log        | 30.0  | 150  | 4.4654          |
  | No log        | 31.0  | 155  | 4.4069          |
  | No log        | 32.0  | 160  | 4.4108          |
  | No log        | 33.0  | 165  | 4.4394          |
  | No log        | 34.0  | 170  | 4.4320          |
  | No log        | 35.0  | 175  | 4.3541          |
  | No log        | 36.0  | 180  | 4.4534          |
  | No log        | 37.0  | 185  | 4.2616          |
  | No log        | 38.0  | 190  | 4.2474          |
  | No log        | 39.0  | 195  | 4.4358          |
  | No log        | 40.0  | 200  | 4.3060          |
  | No log        | 41.0  | 205  | 4.1866          |
  | No log        | 42.0  | 210  | 4.2735          |
  | No log        | 43.0  | 215  | 4.2739          |
  | No log        | 44.0  | 220  | 4.1812          |
  | No log        | 45.0  | 225  | 4.2484          |
  | No log        | 46.0  | 230  | 4.3706          |
  | No log        | 47.0  | 235  | 4.3487          |
  | No log        | 48.0  | 240  | 4.2805          |
  | No log        | 49.0  | 245  | 4.3180          |
  | No log        | 50.0  | 250  | 4.3574          |
  | No log        | 51.0  | 255  | 4.2823          |
  | No log        | 52.0  | 260  | 4.0643          |
  | No log        | 53.0  | 265  | 4.0729          |
  | No log        | 54.0  | 270  | 4.2368          |
  | No log        | 55.0  | 275  | 4.2845          |
  | No log        | 56.0  | 280  | 4.1009          |
  | No log        | 57.0  | 285  | 4.0629          |
  | No log        | 58.0  | 290  | 4.1250          |
  | No log        | 59.0  | 295  | 4.2048          |
  | No log        | 60.0  | 300  | 4.2412          |
  | No log        | 61.0  | 305  | 4.1653          |
  | No log        | 62.0  | 310  | 4.1433          |
  | No log        | 63.0  | 315  | 4.1309          |
  | No log        | 64.0  | 320  | 4.1381          |
  | No log        | 65.0  | 325  | 4.2162          |
  | No log        | 66.0  | 330  | 4.1858          |
  | No log        | 67.0  | 335  | 4.1342          |
  | No log        | 68.0  | 340  | 4.1247          |
  | No log        | 69.0  | 345  | 4.1701          |
  | No log        | 70.0  | 350  | 4.1915          |
  | No log        | 71.0  | 355  | 4.1356          |
  | No log        | 72.0  | 360  | 4.1766          |
  | No log        | 73.0  | 365  | 4.1296          |
  | No log        | 74.0  | 370  | 4.0594          |
  | No log        | 75.0  | 375  | 4.0601          |
  | No log   