README.md

metadata

license: other
tags:
  - generated_from_trainer
datasets:
  - AlekseyKorshuk/amazon-reviews-input-output
metrics:
  - accuracy
model-index:
  - name: amazon-reviews-input-output-1.3b
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: AlekseyKorshuk/amazon-reviews-input-output
          type: AlekseyKorshuk/amazon-reviews-input-output
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.03550813008130081

amazon-reviews-input-output-1.3b

This model is a fine-tuned version of facebook/opt-1.3b on the AlekseyKorshuk/amazon-reviews-input-output dataset. It achieves the following results on the evaluation set:

• Loss: 3.5488
• Accuracy: 0.0355
• Samples: 100
• Perplexity: 34.7725
• Table: <wandb.data_types.Table object at 0x7ffa3c3fd700>

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: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 8
• total_train_batch_size: 64
• total_eval_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
3.2024	0.06	1	2.9121	0.0385
3.1226	0.12	2	2.9121	0.0385
3.1321	0.19	3	2.8477	0.0394
2.9875	0.25	4	2.8477	0.0394
2.9717	0.31	5	2.8555	0.0391
2.9341	0.38	6	2.8438	0.0392
3.0376	0.44	7	2.8184	0.0396
2.8164	0.5	8	2.7988	0.0395
3.0857	0.56	9	2.7988	0.0394
2.9492	0.62	10	2.7969	0.0395
2.8633	0.69	11	2.7969	0.0395
2.8994	0.75	12	2.7910	0.0398
3.0024	0.81	13	2.7812	0.0401
2.937	0.88	14	2.7812	0.0399
2.9963	0.94	15	2.7812	0.0399
3.0168	1.0	16	2.7754	0.04
2.2589	1.06	17	2.7715	0.0397
2.2568	1.12	18	2.7793	0.0395
2.3138	1.19	19	2.8027	0.0393
2.2759	1.25	20	2.8184	0.0393
2.5137	1.31	21	2.8262	0.0390
2.2997	1.38	22	2.8320	0.0388
2.2693	1.44	23	2.8359	0.0392
2.204	1.5	24	2.8379	0.0387
2.3713	1.56	25	2.8359	0.0391
2.3448	1.62	26	2.8340	0.0391
2.217	1.69	27	2.8359	0.0391
2.3082	1.75	28	2.8379	0.0385
2.2878	1.81	29	2.8379	0.0386
2.2429	1.88	30	2.8379	0.0385
2.2838	1.94	31	2.8359	0.0385
2.4038	2.0	32	2.8379	0.0387
1.8481	2.06	33	2.8555	0.0384
1.657	2.12	34	2.8965	0.0382
1.6996	2.19	35	2.9590	0.0380
1.6741	2.25	36	3.0312	0.0379
1.594	2.31	37	3.0410	0.0380
1.5201	2.38	38	3.0156	0.0381
1.5149	2.44	39	3.0137	0.0380
1.5521	2.5	40	3.0176	0.0379
1.5364	2.56	41	3.0273	0.0378
1.5385	2.62	42	3.0391	0.0380
1.4794	2.69	43	3.0488	0.0380
1.4313	2.75	44	3.0527	0.0378
1.5071	2.81	45	3.0469	0.0378
1.4799	2.88	46	3.0449	0.0378
1.521	2.94	47	3.0371	0.0380
1.4603	3.0	48	3.0410	0.0379
1.25	3.06	49	3.0859	0.0381
1.0411	3.12	50	3.1797	0.0375
1.0385	3.19	51	3.2969	0.0371
1.0254	3.25	52	3.3613	0.0367
0.9656	3.31	53	3.3633	0.0368
1.036	3.38	54	3.3359	0.0366
0.9366	3.44	55	3.2949	0.0366
0.9712	3.5	56	3.2695	0.0367
1.0066	3.56	57	3.2676	0.0366
0.9952	3.62	58	3.2773	0.0368
1.0352	3.69	59	3.2891	0.0367
1.0212	3.75	60	3.3164	0.0362
0.9468	3.81	61	3.3203	0.0360
0.9155	3.88	62	3.3223	0.0366
0.8552	3.94	63	3.3262	0.0370
0.9575	4.0	64	3.3340	0.0370
0.6384	4.06	65	3.375	0.0370
0.6436	4.12	66	3.4453	0.0364
0.5752	4.19	67	3.5391	0.0358
0.6542	4.25	68	3.6016	0.0354
0.6724	4.31	69	3.6016	0.0354
0.591	4.38	70	3.5938	0.0359
0.5346	4.44	71	3.5801	0.0361
0.5112	4.5	72	3.5762	0.0361
0.5443	4.56	73	3.5840	0.0362
0.5689	4.62	74	3.6152	0.0358
0.5667	4.69	75	3.6328	0.0358
0.554	4.75	76	3.6348	0.0357
0.6087	4.81	77	3.625	0.0355
0.5236	4.88	78	3.6152	0.0355
0.5458	4.94	79	3.5781	0.0355
0.5702	5.0	80	3.5488	0.0355

Framework versions

• Transformers 4.25.0.dev0
• Pytorch 1.12.1+cu113
• Datasets 2.3.2
• Tokenizers 0.12.1