metadata

tags:
  - generated_from_trainer
datasets:
  - BEE-spoke-data/goodwiki-deduped-split
metrics:
  - accuracy
model-index:
  - name: bitllama-goodwiki
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: BEE-spoke-data/goodwiki-deduped-split
          type: BEE-spoke-data/goodwiki-deduped-split
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.4285134482793542

bitllama-goodwiki

This model was trained from scratch on the BEE-spoke-data/goodwiki-deduped-split dataset. It achieves the following results on the evaluation set:

Loss: 3.0525
Accuracy: 0.4285

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: 0.0008
train_batch_size: 8
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 100
num_epochs: 1.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
6.1199	0.04	100	6.0749	0.1542
5.3869	0.07	200	5.3267	0.2032
4.9187	0.11	300	4.8566	0.2386
4.6185	0.14	400	4.5535	0.2624
4.3509	0.18	500	4.3388	0.2801
4.1666	0.21	600	4.1692	0.2956
4.0456	0.25	700	4.0399	0.3089
3.9273	0.28	800	3.9318	0.3193
3.8447	0.32	900	3.8173	0.3327
3.7143	0.35	1000	3.7108	0.3461
3.6485	0.39	1100	3.6116	0.3590
3.5171	0.42	1200	3.5303	0.3693
3.4464	0.46	1300	3.4554	0.3780
3.3955	0.49	1400	3.3999	0.3851
3.3551	0.53	1500	3.3432	0.3919
3.2787	0.56	1600	3.2981	0.3974
3.2705	0.6	1700	3.2566	0.4023
3.2281	0.64	1800	3.2172	0.4075
3.1759	0.67	1900	3.1826	0.4118
3.1603	0.71	2000	3.1547	0.4152
3.1328	0.74	2100	3.1283	0.4186
3.0916	0.78	2200	3.1055	0.4215
3.0939	0.81	2300	3.0875	0.4238
3.0584	0.85	2400	3.0732	0.4257
3.0711	0.88	2500	3.0631	0.4271
3.0612	0.92	2600	3.0565	0.4280
3.081	0.95	2700	3.0534	0.4284
3.0378	0.99	2800	3.0525	0.4285

Framework versions

Transformers 4.37.2
Pytorch 2.2.0+cu121
Datasets 2.16.1
Tokenizers 0.15.0