
<!-- 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. -->

# odinsynth_encoder_decoder_native_hf_test_2

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the enoriega/odinsynth_sequence_dataset synthetic_surface dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0771
- Accuracy: 0.9343

## 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: 3
- eval_batch_size: 3
- seed: 42
- gradient_accumulation_steps: 200
- total_train_batch_size: 600
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.1612        | 0.67  | 60   | 0.1145          | 0.9376   |
| 0.0666        | 1.34  | 120  | 0.0628          | 0.9356   |
| 0.0599        | 2.01  | 180  | 0.0611          | 0.9355   |
| 0.0563        | 2.68  | 240  | 0.0631          | 0.9352   |
| 0.0512        | 3.35  | 300  | 0.0630          | 0.9347   |
| 0.0472        | 4.02  | 360  | 0.0638          | 0.9338   |
| 0.0438        | 4.69  | 420  | 0.0655          | 0.9339   |
| 0.0405        | 5.36  | 480  | 0.0660          | 0.9345   |
| 0.0378        | 6.03  | 540  | 0.0666          | 0.9342   |
| 0.0344        | 6.69  | 600  | 0.0669          | 0.9343   |
| 0.0323        | 7.36  | 660  | 0.0678          | 0.9344   |
| 0.0307        | 8.03  | 720  | 0.0694          | 0.9343   |
| 0.0294        | 8.7   | 780  | 0.0706          | 0.9345   |
| 0.0286        | 9.37  | 840  | 0.0725          | 0.9342   |
| 0.0275        | 10.04 | 900  | 0.0727          | 0.9343   |
| 0.0282        | 10.71 | 960  | 0.0732          | 0.9342   |
| 0.0264        | 11.38 | 1020 | 0.0735          | 0.9343   |
| 0.026         | 12.05 | 1080 | 0.0750          | 0.9342   |
| 0.0254        | 12.72 | 1140 | 0.0753          | 0.9343   |
| 0.0244        | 13.39 | 1200 | 0.0746          | 0.9344   |
| 0.0242        | 14.06 | 1260 | 0.0752          | 0.9343   |
| 0.024         | 14.73 | 1320 | 0.0758          | 0.9342   |
| 0.0239        | 15.4  | 1380 | 0.0764          | 0.9343   |
| 0.0234        | 16.07 | 1440 | 0.0763          | 0.9343   |
| 0.0231        | 16.74 | 1500 | 0.0764          | 0.9343   |
| 0.0226        | 17.41 | 1560 | 0.0770          | 0.9343   |
| 0.023         | 18.08 | 1620 | 0.0770          | 0.9343   |
| 0.0227        | 18.74 | 1680 | 0.0771          | 0.9343   |
| 0.0221        | 19.41 | 1740 | 0.0771          | 0.9343   |


### Framework versions

- Transformers 4.27.4
- Pytorch 2.0.0
- Datasets 2.11.0
- Tokenizers 0.11.0

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["enoriega/odinsynth_sequence_dataset"], "metrics": ["accuracy"], "model-index": [{"name": "odinsynth_encoder_decoder_native_hf_test_2", "results": [{"task": {"type": "text-generation", "name": "Causal Language Modeling"}, "dataset": {"name": "enoriega/odinsynth_sequence_dataset synthetic_surface", "type": "enoriega/odinsynth_sequence_dataset", "config": "synthetic_surface", "split": "validation", "args": "synthetic_surface"}, "metrics": [{"type": "accuracy", "value": 0.9343159108876246, "name": "Accuracy"}]}]}]}
transformers pytorch tensorboard encoder-decoder text2text-generation generated_from_trainer dataset:enoriega/odinsynth_sequence_dataset license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #generated_from_trainer #dataset-enoriega/odinsynth_sequence_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 

odinsynth\_encoder\_decoder\_native\_hf\_test\_2
================================================


This model is a fine-tuned version of bert-base-uncased on the enoriega/odinsynth\_sequence\_dataset synthetic\_surface dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0771
* Accuracy: 0.9343


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: 3
* eval\_batch\_size: 3
* seed: 42
* gradient\_accumulation\_steps: 200
* total\_train\_batch\_size: 600
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0


### Training results



### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* Tokenizers 0.11.0



### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 3
* eval\_batch\_size: 3
* seed: 42
* gradient\_accumulation\_steps: 200
* total\_train\_batch\_size: 600
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #generated_from_trainer #dataset-enoriega/odinsynth_sequence_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 3
* eval\_batch\_size: 3
* seed: 42
* gradient\_accumulation\_steps: 200
* total\_train\_batch\_size: 600
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0 ### Training results ### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* Tokenizers 0.11.0
TAGS
#transformers #pytorch #tensorboard #encoder-decoder #text2text-generation #generated_from_trainer #dataset-enoriega/odinsynth_sequence_dataset #license-apache-2.0 #model-index #autotrain_compatible #endpoints_compatible #region-us 
### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 5e-05
* train\_batch\_size: 3
* eval\_batch\_size: 3
* seed: 42
* gradient\_accumulation\_steps: 200
* total\_train\_batch\_size: 600
* optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
* lr\_scheduler\_type: linear
* num\_epochs: 20.0### Training results### Framework versions


* Transformers 4.27.4
* Pytorch 2.0.0
* Datasets 2.11.0
* Tokenizers 0.11.0