The Model Fine-Tuning Token Budget Planner estimates the total training-token volume for a fine-tuning run, including repeated epochs and optional validation data. It also converts the token total into an estimated training charge when a price per million tokens is supplied.
Use it to compare dataset sizes, epoch counts, and budget scenarios before starting a job. The planner treats token counts as already prepared and does not estimate tokenizer-specific expansion from raw text.
1. Count training examples
Enter the number of prepared examples before the validation split.
2. Estimate token length
Use the tokenizer-specific average token count per example.
3. Set epochs
Enter how many times the training subset will be processed.
4. Add validation share
Specify the portion held out from training; it is counted once in this planning model.
5. Enter training price
Use zero if only token volume is needed.
The main result is the total token volume processed under the stated training and validation assumptions.
Provider billing may count validation, checkpoints, or special tokens differently; use the pricing definition from the selected platform.
Given: 50,000 examples, 800 tokens each, 3 epochs, 10% validation, and $8 per million training tokens.
Calculation: Base tokens = 40,000,000. Training tokens = 40,000,000 × 0.90 × 3 = 108,000,000. Validation tokens = 4,000,000. Total = 112,000,000 tokens. Estimated training cost = 108 × $8 = $864.
Result: Plan for 112 million processed tokens and about $864 in training-token charges.
It should include every token passed to training for one example, including prompts, responses, and formatting tokens.
This planner uses a simple one-pass validation assumption. Platforms that evaluate every epoch may process more validation tokens.
Not reliably. Token counts depend on language, formatting, and tokenizer, so direct tokenization is preferable.
Training-token volume increases approximately in direct proportion to the epoch count.
No. Use the final cleaned dataset that will actually enter the training job.